diff --git a/_downloads/5fdddbed2260616231dbf7b0d94bb665/train.txt b/_downloads/5fdddbed2260616231dbf7b0d94bb665/train.txt
index ca83ac6e0..c091a5934 100644
--- a/_downloads/5fdddbed2260616231dbf7b0d94bb665/train.txt
+++ b/_downloads/5fdddbed2260616231dbf7b0d94bb665/train.txt
@@ -1,17 +1,17 @@
-2024-04-14 13:46:21 (INFO): Project root: /home/runner/work/ocp/ocp
+2024-04-14 18:46:02 (INFO): Project root: /home/runner/work/ocp/ocp
/opt/hostedtoolcache/Python/3.11.9/x64/lib/python3.11/site-packages/torch/cuda/amp/grad_scaler.py:126: UserWarning: torch.cuda.amp.GradScaler is enabled, but CUDA is not available. Disabling.
warnings.warn(
-2024-04-14 13:46:23 (WARNING): Detected old config, converting to new format. Consider updating to avoid potential incompatibilities.
-2024-04-14 13:46:23 (INFO): amp: true
+2024-04-14 18:46:03 (WARNING): Detected old config, converting to new format. Consider updating to avoid potential incompatibilities.
+2024-04-14 18:46:03 (INFO): amp: true
cmd:
- checkpoint_dir: fine-tuning/checkpoints/2024-04-14-13-45-36-ft-oxides
- commit: b90c171
+ checkpoint_dir: fine-tuning/checkpoints/2024-04-14-18-46-24-ft-oxides
+ commit: 962bffa
identifier: ft-oxides
- logs_dir: fine-tuning/logs/wandb/2024-04-14-13-45-36-ft-oxides
+ logs_dir: fine-tuning/logs/wandb/2024-04-14-18-46-24-ft-oxides
print_every: 10
- results_dir: fine-tuning/results/2024-04-14-13-45-36-ft-oxides
+ results_dir: fine-tuning/results/2024-04-14-18-46-24-ft-oxides
seed: 0
- timestamp_id: 2024-04-14-13-45-36-ft-oxides
+ timestamp_id: 2024-04-14-18-46-24-ft-oxides
dataset:
a2g_args:
r_energy: true
diff --git a/_images/039ed970e0b1e654d1c5696394765bdfbb15ef84d1d3062637148bd4f0927ff8.png b/_images/039ed970e0b1e654d1c5696394765bdfbb15ef84d1d3062637148bd4f0927ff8.png
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diff --git a/_images/e1d30625e6e60fa80387151aa238daa23502da4d794234ef3a02ebfd05b700e1.png b/_images/e1d30625e6e60fa80387151aa238daa23502da4d794234ef3a02ebfd05b700e1.png
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diff --git a/_sources/core/inference.md b/_sources/core/inference.md
index ee8fb7be8..265c30787 100644
--- a/_sources/core/inference.md
+++ b/_sources/core/inference.md
@@ -11,7 +11,7 @@ kernelspec:
name: python3
---
-Mass inference
+Fast batched inference
------------------
The ASE calculator is not necessarily the most efficient way to run a lot of computations. It is better to do a "mass inference" using a command line utility. We illustrate how to do that here.
diff --git a/_sources/videos/intro_series.md b/_sources/core/intro_series.md
similarity index 97%
rename from _sources/videos/intro_series.md
rename to _sources/core/intro_series.md
index edf57817a..60e8d3559 100644
--- a/_sources/videos/intro_series.md
+++ b/_sources/core/intro_series.md
@@ -1,4 +1,4 @@
-# Open Catalyst Intro Series
+# Why model atoms for climate?
New to chemistry but excited to know how ML can help? Larry Zitnick has made a few intro videos for audiences without a computational chemistry background!
diff --git a/_sources/tutorials/adsorbml_walkthrough.md b/_sources/tutorials/adsorbml_walkthrough.md
index 8160da507..4996afbfe 100644
--- a/_sources/tutorials/adsorbml_walkthrough.md
+++ b/_sources/tutorials/adsorbml_walkthrough.md
@@ -204,6 +204,9 @@ idxs_to_keep = deduplicate(configs_for_deduplication, adsorbate.binding_indices[
```
```{code-cell} ipython3
+---
+tags: ["skip-execution"]
+---
# Flip through your configurations to check them out (and make sure deduplication looks good)
print(idxs_to_keep)
view_x3d_n(configs_for_deduplication[2].repeat((2,2,1)))
@@ -221,9 +224,12 @@ df
## Write VASP input files
-This assumes you have access to VASP pseudopotentials. The default VASP flags (which are equivalent to those used to make OC20) are located in `ocdata.utils.vasp`. Alternatively, you may pass your own vasp flags to the `write_vasp_input_files` function as `vasp_flags`
+This assumes you have access to VASP pseudopotentials and the right environment variables configured for ASE. The default VASP flags (which are equivalent to those used to make OC20) are located in `ocdata.utils.vasp`. Alternatively, you may pass your own vasp flags to the `write_vasp_input_files` function as `vasp_flags`.
```{code-cell} ipython3
+---
+tags: ["skip-execution"]
+---
# Grab the 5 systems with the lowest energy
configs_for_dft = df.sort_values(by = "relaxed_energy_ml").relaxed_atoms.tolist()[0:5]
config_idxs = df.sort_values(by = "relaxed_energy_ml").relaxation_idx.tolist()[0:5]
diff --git a/_sources/tutorials/advanced/embeddings.md b/_sources/tutorials/advanced/embeddings.md
index 0b58ef929..7eadd9108 100644
--- a/_sources/tutorials/advanced/embeddings.md
+++ b/_sources/tutorials/advanced/embeddings.md
@@ -20,7 +20,11 @@ OCP works by computing an *embedding*, aka a high dimensional vector representat
We used them to search for similar atomic structures.
-We can use them for diagnostic purposes, or clustering. For GemNet-OC, we provide 5 different kinds of embeddings:
+We can use them for diagnostic purposes, or clustering.
+
+In this example, we patch the GemNetOC model to save the embeddings so you can easily access them. This requires two changes. The first is in the GemNetOC model where the embeddings are saved, and the second is in the OCPCalculator to retrieve them.
+
+We provide 5 different kinds of embeddings:
1. 'h' - This is an early block in the embedding calculation. You get the h-embedding for each atom
2. 'h sum' - This is an early block in the embedding calculation. You get the h-embedding summed over each atom
@@ -28,7 +32,13 @@ We can use them for diagnostic purposes, or clustering. For GemNet-OC, we provid
4. 'x_E sum' - summed over atoms
5. 'x_F sum' - This is related to the forces
-In principle other models could be adapted in a similar way.
+In principle other models could be adapted in a similar way. See [embedding-monkeypatch.py](./embedding-monkeypatch.py) for details on the patch. We simply run this notebook below to load it.
+
+The OCP project is still under active development, and it is not yet clear what the best way to access these embeddings are, so this code is not yet part of the main development branch. This code was adapted from a branch at https://github.com/Open-Catalyst-Project/ocp/blob/gnoc-embeddings.
+
+```{code-cell} ipython3
+import embedding_monkeypatch
+```
# A diagnostic example
@@ -49,8 +59,6 @@ import os
checkpoint_path = model_name_to_local_file('GemNet-OCOC20+OC22', local_cache='/tmp/ocp_checkpoints/')
calc = OCPCalculator(checkpoint_path=checkpoint_path)
-calc.trainer._unwrapped_model.return_embedding = True
-
```
## Bulk Cu equation of state example
@@ -58,6 +66,7 @@ calc.trainer._unwrapped_model.return_embedding = True
Here we simply compute an equation of state by varying the lattice constant. You will see a small unphysical feature near 3.7 angstroms. We will investigate why that happens.
```{code-cell} ipython3
+#calc.trainer._unwrapped_model.return_embedding = False
a0 = 3.63
E = []
@@ -79,7 +88,7 @@ plt.xlabel('Lattice constant (A)')
plt.ylabel('Energy (eV)');
```
-Something is a little off in this equation of state, there is an unphysical bump in it. We now rerun this and get the embeddings. You simply set `calc.trainer._unwrapped_model.return_embedding = True` and the calculator will return useful embeddings if possible (e.g. for GemNet-OC). We need a reference configuration to compare too. We choose a lattice constant of 3.63 angstroms and compute three different embeddings.
+Something is a little off in this equation of state, there is an unphysical bump in it. We now rerun this and get the embeddings. You simply call the `calc.embed` method. We need a reference configuration to compare too. We choose a lattice constant of 3.63 angstroms and compute three different embeddings.
```{code-cell} ipython3
a0 = 3.63
@@ -92,9 +101,9 @@ atoms = atoms.repeat((2, 2, 2))
atoms.set_tags(np.ones(len(atoms)))
atoms.calc = calc
-atoms.get_potential_energy()
+out = calc.embed(atoms)
-x1, x2, x3 = atoms.calc.results['h sum'], atoms.calc.results['x_E sum'], atoms.calc.results['x_F sum']
+x1, x2, x3 = out['h sum'], out['x_E sum'], out['x_F sum']
```
Next, we loop over a grid of lattice constants, and we compare the cosine similarity of the embeddings for each one to the reference embeddings above. A similarity of 1 means they are the same, and as the similarity decreases it means the embbedings are more and more different (and so is the energy).
@@ -112,12 +121,12 @@ for a in LC:
pbc=True)
atoms = atoms.repeat((2, 2, 2))
atoms.set_tags(np.ones(len(atoms)))
- atoms.get_potential_energy()
+ out = calc.embed(atoms)
- cossim1.append(torch.cosine_similarity(x1, atoms.calc.results["h sum"]).item())
- cossim2.append(torch.cosine_similarity(x2, atoms.calc.results["x_E sum"]).item())
- cossim3.append(torch.cosine_similarity(x3, atoms.calc.results["x_F sum"]).item())
+ cossim1.append(torch.cosine_similarity(x1, out["h sum"]).item())
+ cossim2.append(torch.cosine_similarity(x2, out["x_E sum"]).item())
+ cossim3.append(torch.cosine_similarity(x3, out["x_F sum"]).item())
E += [out['energy']]
```
@@ -153,17 +162,17 @@ We use this example to show that we can cluster structures by embedding similari
from ase.build import bulk
from ase.cluster import Octahedron
+calc.trainer._unwrapped_model.return_embedding = True
+
embeddings = []
labels = []
oct = Octahedron('Cu', 2)
oct.set_tags(np.ones(len(oct)))
-oct.calc = calc
for i in range(20):
oct.rattle(0.01)
- oct.get_potential_energy()
- embeddings += [oct.calc.results['x_E sum'][0].numpy()]
+ embeddings += [calc.embed(oct)['x_E sum'][0].numpy()]
labels += [0]
```
@@ -171,11 +180,10 @@ for i in range(20):
b = bulk('Cu')
b = b.repeat((2, 2, 2))
b.set_tags(np.ones(len(b)))
-b.calc = calc
for i in range(40):
b.rattle(0.01)
- embeddings += [b.calc.results['x_E sum'][0].numpy()]
+ embeddings += [calc.embed(b)['x_E sum'][0].numpy()]
labels += [1]
```
@@ -213,15 +221,14 @@ energies = []
oct = Octahedron('Cu', 2)
oct.set_tags(np.ones(len(oct)))
-oct.calc = calc
+
for i in range(20):
oct.rattle(0.01)
- oct.get_potential_energy()
-
- for a in oct.calc.results['h'][0]:
+ out = calc.embed(oct)
+ for a in out['h'][0]:
embeddings += [a.numpy()]
labels += [0]
- energies += [oct.calc.results['energy']]
+ energies += [out['energy']]
b = bulk('Cu')
b = b.repeat((2, 2, 2))
@@ -229,12 +236,11 @@ b.set_tags(np.ones(len(b)))
for i in range(20):
b.rattle(0.01)
- b.get_potential_energy()
-
- for a in b.calc.results['h'][0]:
+ out = calc.embed(b)
+ for a in out['h'][0]:
embeddings += [a.numpy()]
labels += [1]
- energies += [b.calc.results['energy']]
+ energies += [out['energy']]
embeddings = np.array(embeddings)
@@ -270,20 +276,17 @@ data = vdict(space='cosine')
ethanol = molecule('CH3CH2OH')
ethanol.set_tags(np.ones(len(ethanol)))
-ethanol.calc = calc
-ethanol.get_potential_energy()
-
-for i, atom in enumerate(ethanol):
- data[ethanol.calc.results['x_E'][0][i].numpy()] = [i, ethanol]
-
+ethanol_emb = calc.embed(ethanol)
methane = molecule('C2H6')
methane.set_tags(np.ones(len(methane)))
-methane.calc = calc
-methane.get_potential_energy()
+methane_emb = calc.embed(methane)
+for i, atom in enumerate(ethanol):
+ data[ethanol_emb['x_E'][0][i].numpy()] = [i, ethanol]
+
for i, atom in enumerate(methane):
- data[methane.calc.results['x_E'][0][i].numpy()] = [i, methane]
+ data[methane_emb['x_E'][0][i].numpy()] = [i, methane]
```
Now we construct our "query". We inspect the Atoms object, see that the C atom is the first one, and then extract the embedding for that atom and save it in a variable.
@@ -291,14 +294,12 @@ Now we construct our "query". We inspect the Atoms object, see that the C atom i
```{code-cell} ipython3
methanol = molecule('CH3OH')
methanol.set_tags(np.ones(len(methanol)))
-methanol.calc = calc
-methanol.get_potential_energy()
-
+methanol_emb = calc.embed(methanol)
methanol
```
```{code-cell} ipython3
-query = methanol.calc.results['x_E'][0][0].numpy()
+query = methanol_emb['x_E'][0][0].numpy()
```
We run our search with the syntax like a dictionary. It returns the closest found match.
diff --git a/autoapi/index.html b/autoapi/index.html
index 3a767ff5a..4030573ce 100644
--- a/autoapi/index.html
+++ b/autoapi/index.html
@@ -216,7 +216,7 @@
Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
Case Studies & Tutorials
diff --git a/autoapi/ocpmodels/common/data_parallel/index.html b/autoapi/ocpmodels/common/data_parallel/index.html
index 2f3b044a0..e7fe0cda0 100644
--- a/autoapi/ocpmodels/common/data_parallel/index.html
+++ b/autoapi/ocpmodels/common/data_parallel/index.html
@@ -216,7 +216,7 @@
Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
Case Studies & Tutorials
diff --git a/autoapi/ocpmodels/common/distutils/index.html b/autoapi/ocpmodels/common/distutils/index.html
index b621f1f69..a7a91aa62 100644
--- a/autoapi/ocpmodels/common/distutils/index.html
+++ b/autoapi/ocpmodels/common/distutils/index.html
@@ -216,7 +216,7 @@
Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
Case Studies & Tutorials
diff --git a/autoapi/ocpmodels/common/flags/index.html b/autoapi/ocpmodels/common/flags/index.html
index cb3a135d5..847484820 100644
--- a/autoapi/ocpmodels/common/flags/index.html
+++ b/autoapi/ocpmodels/common/flags/index.html
@@ -216,7 +216,7 @@
Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
Case Studies & Tutorials
diff --git a/autoapi/ocpmodels/common/gp_utils/index.html b/autoapi/ocpmodels/common/gp_utils/index.html
index abf0d4c4a..23b29cf11 100644
--- a/autoapi/ocpmodels/common/gp_utils/index.html
+++ b/autoapi/ocpmodels/common/gp_utils/index.html
@@ -216,7 +216,7 @@
Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
Case Studies & Tutorials
diff --git a/autoapi/ocpmodels/common/hpo_utils/index.html b/autoapi/ocpmodels/common/hpo_utils/index.html
index f8fc5b0ff..5c4354711 100644
--- a/autoapi/ocpmodels/common/hpo_utils/index.html
+++ b/autoapi/ocpmodels/common/hpo_utils/index.html
@@ -216,7 +216,7 @@
Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
Case Studies & Tutorials
diff --git a/autoapi/ocpmodels/common/index.html b/autoapi/ocpmodels/common/index.html
index 95cccbfa3..7f9144e7e 100644
--- a/autoapi/ocpmodels/common/index.html
+++ b/autoapi/ocpmodels/common/index.html
@@ -216,7 +216,7 @@
Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
Case Studies & Tutorials
diff --git a/autoapi/ocpmodels/common/logger/index.html b/autoapi/ocpmodels/common/logger/index.html
index 723aa02c5..37a1ba5f1 100644
--- a/autoapi/ocpmodels/common/logger/index.html
+++ b/autoapi/ocpmodels/common/logger/index.html
@@ -216,7 +216,7 @@
Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
Case Studies & Tutorials
diff --git a/autoapi/ocpmodels/common/registry/index.html b/autoapi/ocpmodels/common/registry/index.html
index 11965bfb1..de386f66d 100644
--- a/autoapi/ocpmodels/common/registry/index.html
+++ b/autoapi/ocpmodels/common/registry/index.html
@@ -216,7 +216,7 @@
Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
Case Studies & Tutorials
diff --git a/autoapi/ocpmodels/common/relaxation/ase_utils/index.html b/autoapi/ocpmodels/common/relaxation/ase_utils/index.html
index 83a2e7fa6..5da6a6960 100644
--- a/autoapi/ocpmodels/common/relaxation/ase_utils/index.html
+++ b/autoapi/ocpmodels/common/relaxation/ase_utils/index.html
@@ -216,7 +216,7 @@
Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
Case Studies & Tutorials
diff --git a/autoapi/ocpmodels/common/relaxation/index.html b/autoapi/ocpmodels/common/relaxation/index.html
index 9b862bc1e..fed0fdf73 100644
--- a/autoapi/ocpmodels/common/relaxation/index.html
+++ b/autoapi/ocpmodels/common/relaxation/index.html
@@ -216,7 +216,7 @@
Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
Case Studies & Tutorials
diff --git a/autoapi/ocpmodels/common/relaxation/ml_relaxation/index.html b/autoapi/ocpmodels/common/relaxation/ml_relaxation/index.html
index 62fcf4b52..d13b98b54 100644
--- a/autoapi/ocpmodels/common/relaxation/ml_relaxation/index.html
+++ b/autoapi/ocpmodels/common/relaxation/ml_relaxation/index.html
@@ -216,7 +216,7 @@
Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
Case Studies & Tutorials
diff --git a/autoapi/ocpmodels/common/relaxation/optimizers/index.html b/autoapi/ocpmodels/common/relaxation/optimizers/index.html
index 9c61a3b52..db2ccc4c3 100644
--- a/autoapi/ocpmodels/common/relaxation/optimizers/index.html
+++ b/autoapi/ocpmodels/common/relaxation/optimizers/index.html
@@ -216,7 +216,7 @@
Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
Case Studies & Tutorials
diff --git a/autoapi/ocpmodels/common/relaxation/optimizers/lbfgs_torch/index.html b/autoapi/ocpmodels/common/relaxation/optimizers/lbfgs_torch/index.html
index 7d46e4f8e..644ae5631 100644
--- a/autoapi/ocpmodels/common/relaxation/optimizers/lbfgs_torch/index.html
+++ b/autoapi/ocpmodels/common/relaxation/optimizers/lbfgs_torch/index.html
@@ -216,7 +216,7 @@
Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
Case Studies & Tutorials
diff --git a/autoapi/ocpmodels/common/transforms/index.html b/autoapi/ocpmodels/common/transforms/index.html
index bbf6bb2a2..8bbd485d6 100644
--- a/autoapi/ocpmodels/common/transforms/index.html
+++ b/autoapi/ocpmodels/common/transforms/index.html
@@ -218,7 +218,7 @@
Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
Case Studies & Tutorials
diff --git a/autoapi/ocpmodels/common/tutorial_utils/index.html b/autoapi/ocpmodels/common/tutorial_utils/index.html
index 6333484d1..b63af3950 100644
--- a/autoapi/ocpmodels/common/tutorial_utils/index.html
+++ b/autoapi/ocpmodels/common/tutorial_utils/index.html
@@ -216,7 +216,7 @@
Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
Case Studies & Tutorials
diff --git a/autoapi/ocpmodels/common/typing/index.html b/autoapi/ocpmodels/common/typing/index.html
index 57e0c051c..8399f4d14 100644
--- a/autoapi/ocpmodels/common/typing/index.html
+++ b/autoapi/ocpmodels/common/typing/index.html
@@ -216,7 +216,7 @@
Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
Case Studies & Tutorials
diff --git a/autoapi/ocpmodels/common/utils/index.html b/autoapi/ocpmodels/common/utils/index.html
index ee3e94efe..2c671b6ac 100644
--- a/autoapi/ocpmodels/common/utils/index.html
+++ b/autoapi/ocpmodels/common/utils/index.html
@@ -216,7 +216,7 @@
Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
Case Studies & Tutorials
diff --git a/autoapi/ocpmodels/datasets/_utils/index.html b/autoapi/ocpmodels/datasets/_utils/index.html
index ea79ef75f..7525d6427 100644
--- a/autoapi/ocpmodels/datasets/_utils/index.html
+++ b/autoapi/ocpmodels/datasets/_utils/index.html
@@ -216,7 +216,7 @@
Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
Case Studies & Tutorials
diff --git a/autoapi/ocpmodels/datasets/ase_datasets/index.html b/autoapi/ocpmodels/datasets/ase_datasets/index.html
index d8dacc3eb..067d28c6a 100644
--- a/autoapi/ocpmodels/datasets/ase_datasets/index.html
+++ b/autoapi/ocpmodels/datasets/ase_datasets/index.html
@@ -216,7 +216,7 @@
Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
Case Studies & Tutorials
diff --git a/autoapi/ocpmodels/datasets/embeddings/atomic_radii/index.html b/autoapi/ocpmodels/datasets/embeddings/atomic_radii/index.html
index e643ae875..389fbbd9d 100644
--- a/autoapi/ocpmodels/datasets/embeddings/atomic_radii/index.html
+++ b/autoapi/ocpmodels/datasets/embeddings/atomic_radii/index.html
@@ -216,7 +216,7 @@
Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
Case Studies & Tutorials
diff --git a/autoapi/ocpmodels/datasets/embeddings/continuous_embeddings/index.html b/autoapi/ocpmodels/datasets/embeddings/continuous_embeddings/index.html
index fe2950e26..89869971f 100644
--- a/autoapi/ocpmodels/datasets/embeddings/continuous_embeddings/index.html
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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diff --git a/autoapi/ocpmodels/index.html b/autoapi/ocpmodels/index.html
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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@@ -216,7 +216,7 @@
Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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index 11aa14f89..e94c118ee 100644
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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diff --git a/autoapi/ocpmodels/models/gemnet_oc/layers/embedding_block/index.html b/autoapi/ocpmodels/models/gemnet_oc/layers/embedding_block/index.html
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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diff --git a/autoapi/ocpmodels/models/gemnet_oc/layers/force_scaler/index.html b/autoapi/ocpmodels/models/gemnet_oc/layers/force_scaler/index.html
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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diff --git a/autoapi/ocpmodels/models/index.html b/autoapi/ocpmodels/models/index.html
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
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diff --git a/autoapi/ocpmodels/preprocessing/index.html b/autoapi/ocpmodels/preprocessing/index.html
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
Case Studies & Tutorials
diff --git a/autoapi/ocpmodels/tasks/index.html b/autoapi/ocpmodels/tasks/index.html
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
Case Studies & Tutorials
diff --git a/autoapi/ocpmodels/tasks/task/index.html b/autoapi/ocpmodels/tasks/task/index.html
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
Case Studies & Tutorials
diff --git a/autoapi/ocpmodels/trainers/base_trainer/index.html b/autoapi/ocpmodels/trainers/base_trainer/index.html
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
Case Studies & Tutorials
diff --git a/autoapi/ocpmodels/trainers/index.html b/autoapi/ocpmodels/trainers/index.html
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
Case Studies & Tutorials
diff --git a/autoapi/ocpmodels/trainers/ocp_trainer/index.html b/autoapi/ocpmodels/trainers/ocp_trainer/index.html
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
Case Studies & Tutorials
diff --git a/core/ase_dataset_creation.html b/core/ase_dataset_creation.html
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
Case Studies & Tutorials
diff --git a/core/datasets/oc20.html b/core/datasets/oc20.html
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
Case Studies & Tutorials
diff --git a/core/datasets/oc22.html b/core/datasets/oc22.html
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
Case Studies & Tutorials
diff --git a/core/datasets/odac.html b/core/datasets/odac.html
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
Case Studies & Tutorials
diff --git a/core/fine-tuning/fine-tuning-oxides.html b/core/fine-tuning/fine-tuning-oxides.html
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Training and evaluating custom models on OCP datasets Mass inference Fast batched inference Fine tuning a model Videos and Talks
Case Studies & Tutorials
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