ChatGLM2 (#35)

* Update download_model.py

* Update download_model.py

* chatglm2

* Create chatglm2_predictor.py

* Update chatglm2_predictor.py

* Update chatglm2_predictor.py

* Update app.py

* Update chatglm2_predictor.py

* Update chatglm_predictor.py

* Update download_model.py

* Update chatglm2_predictor.py

* Update download_model.py

* Update chatglm2_predictor.py

* Update app.py

* Update chatglm2_predictor.py

* Update chatglm2_predictor.py

* Update chatglm2_predictor.py

app.py

@@ -8,10 +8,12 @@
 print('Done'.center(64, '-'))
 
 # 加载模型
-model_name = 'THUDM/chatglm-6b'
-# model_name = 'silver/chatglm-6b-int4-slim'
+model_name = 'THUDM/chatglm2-6b'
 
-if 'chatglm' in model_name.lower():
+if 'chatglm2' in model_name.lower():
+    from predictors.chatglm2_predictor import ChatGLM2
+    predictor = ChatGLM2(model_name)
+elif 'chatglm' in model_name.lower():
     from predictors.chatglm_predictor import ChatGLM
     predictor = ChatGLM(model_name)
 elif 'gptq' in model_name.lower():

chatglm2/configuration_chatglm.py

@@ -0,0 +1,55 @@
+from transformers import PretrainedConfig
+
+
+class ChatGLMConfig(PretrainedConfig):
+    model_type = "chatglm"
+    def __init__(
+        self,
+        num_layers=28,
+        padded_vocab_size=65024,
+        hidden_size=4096,
+        ffn_hidden_size=13696,
+        kv_channels=128,
+        num_attention_heads=32,
+        seq_length=2048,
+        hidden_dropout=0.0,
+        attention_dropout=0.0,
+        layernorm_epsilon=1e-5,
+        rmsnorm=True,
+        apply_residual_connection_post_layernorm=False,
+        post_layer_norm=True,
+        add_bias_linear=False,
+        add_qkv_bias=False,
+        interleaved_qkv=False,
+        bias_dropout_fusion=True,
+        multi_query_attention=False,
+        multi_query_group_num=1,
+        apply_query_key_layer_scaling=True,
+        attention_softmax_in_fp32=True,
+        fp32_residual_connection=False,
+        quantization_bit=0,
+        **kwargs
+    ):
+        self.num_layers = num_layers
+        self.padded_vocab_size = padded_vocab_size
+        self.hidden_size = hidden_size
+        self.ffn_hidden_size = ffn_hidden_size
+        self.kv_channels = kv_channels
+        self.num_attention_heads = num_attention_heads
+        self.seq_length = seq_length
+        self.hidden_dropout = hidden_dropout
+        self.attention_dropout = attention_dropout
+        self.layernorm_epsilon = layernorm_epsilon
+        self.rmsnorm = rmsnorm
+        self.apply_residual_connection_post_layernorm = apply_residual_connection_post_layernorm
+        self.post_layer_norm = post_layer_norm
+        self.add_bias_linear = add_bias_linear
+        self.add_qkv_bias = add_qkv_bias
+        self.bias_dropout_fusion = bias_dropout_fusion
+        self.multi_query_attention = multi_query_attention
+        self.multi_query_group_num = multi_query_group_num
+        self.apply_query_key_layer_scaling = apply_query_key_layer_scaling
+        self.attention_softmax_in_fp32 = attention_softmax_in_fp32
+        self.fp32_residual_connection = fp32_residual_connection
+        self.quantization_bit = quantization_bit
+        super().__init__(**kwargs)