支持ChatGLM3，版本升级 (#44)

* Update download_model.py

* Create start_offline_cmd.bat

* Update download_model.py

* Update download_model.py

* Update download_model.py

* Update requirements.txt

* Create test_models.py

* Update app.py

* Update test_models.py

* 1

* Create chatglm3_predictor.py

* Update chatglm3_predictor.py

* Update requirements.txt

* Update app.py

* Update chatglm3_predictor.py

* Update base.py

* Update chatglm3_predictor.py

* Update chatglm3_predictor.py

* Update download_model.py

* Update chatglm3_predictor.py

* Update base.py

* Update base.py

* Update base.py

* Update app.py

* Update chatglm3_predictor.py

* Update app.py

Author: ypwhs

app.py

@@ -8,9 +8,12 @@
 print('Done'.center(64, '-'))
 
 # 加载模型
-model_name = 'THUDM/chatglm2-6b'
+model_name = 'THUDM/chatglm3-6b'
 
-if 'chatglm2' in model_name.lower():
+if 'chatglm3' in model_name.lower():
+    from predictors.chatglm3_predictor import ChatGLM3
+    predictor = ChatGLM3(model_name)
+elif 'chatglm2' in model_name.lower():
     from predictors.chatglm2_predictor import ChatGLM2
     predictor = ChatGLM2(model_name)
 elif 'chatglm' in model_name.lower():
@@ -31,7 +34,10 @@
 
 
 def revise(history, latest_message):
-    history[-1] = (history[-1][0], latest_message)
+    if isinstance(history[-1], tuple):
+        history[-1] = (history[-1][0], latest_message)
+    elif isinstance(history[-1], dict):
+        history[-1]['content'] = latest_message
     return history, ''
 
 
@@ -76,21 +82,21 @@ def regenerate(last_state, max_length, top_p, temperature, allow_generate):
 """)
     with gr.Row():
         with gr.Column(scale=4):
-            chatbot = gr.Chatbot(elem_id="chat-box", show_label=False).style(height=850)
+            chatbot = gr.Chatbot(elem_id="chat-box", show_label=False, height=850)
         with gr.Column(scale=1):
             with gr.Row():
                 max_length = gr.Slider(32, 4096, value=2048, step=1.0, label="Maximum length", interactive=True)
                 top_p = gr.Slider(0.01, 1, value=0.7, step=0.01, label="Top P", interactive=True)
                 temperature = gr.Slider(0.01, 5, value=0.95, step=0.01, label="Temperature", interactive=True)
             with gr.Row():
-                query = gr.Textbox(show_label=False, placeholder="Prompts", lines=4).style(container=False)
+                query = gr.Textbox(show_label=False, placeholder="Prompts", lines=4)
                 generate_button = gr.Button("生成")
             with gr.Row():
                 continue_message = gr.Textbox(
-                    show_label=False, placeholder="Continue message", lines=2).style(container=False)
+                    show_label=False, placeholder="Continue message", lines=2)
                 continue_btn = gr.Button("续写")
                 revise_message = gr.Textbox(
-                    show_label=False, placeholder="Revise message", lines=2).style(container=False)
+                    show_label=False, placeholder="Revise message", lines=2)
                 revise_btn = gr.Button("修订")
                 revoke_btn = gr.Button("撤回")
                 regenerate_btn = gr.Button("重新生成")
@@ -114,5 +120,5 @@ def regenerate(last_state, max_length, top_p, temperature, allow_generate):
                          outputs=[chatbot, query, continue_message])
     interrupt_btn.click(interrupt, inputs=[allow_generate])
 
-demo.queue(concurrency_count=4).launch(server_name='0.0.0.0', server_port=7860, share=False, inbrowser=False)
+demo.queue().launch(server_name='0.0.0.0', server_port=7860, share=False, inbrowser=False)
 demo.close()

chatglm3/configuration_chatglm.py

@@ -0,0 +1,61 @@
+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,
+        classifier_dropout=None,
+        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,
+        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,
+        pre_seq_len=None,
+        prefix_projection=False,
+        **kwargs
+    ):
+        self.num_layers = num_layers
+        self.vocab_size = padded_vocab_size
+        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.classifier_dropout = classifier_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
+        self.pre_seq_len = pre_seq_len
+        self.prefix_projection = prefix_projection
+        super().__init__(**kwargs)