Upload model.py

model.py

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+
+from typing import Iterator
+
+
+
+model_id = 'shaowenchen/baichuan2-7b-chat-gguf'
+
+from huggingface_hub import snapshot_download,hf_hub_download
+
+hf_hub_download(model_id, local_dir="./", filename="baichuan2-7b-chat.Q4_K.gguf")
+hf_hub_download(repo_id="baichuan-inc/Baichuan-13B-Chat",local_dir="./", filename="tokenizer.model")
+from llama_cpp import Llama
+llm = Llama(model_path="./baichuan2-7b-chat.Q4_K.gguf", n_ctx=4096,seed=-1)
+
+def run(message: str,
+        chat_history: list[tuple[str, str]],
+        system_prompt: str,
+        max_new_tokens: int = 1024,
+        temperature: float = 0.3,
+        top_p: float = 0.85,
+        top_k: int = 5) -> Iterator[str]:
+    history = []
+    print(chat_history)
+    result=""
+    for i in chat_history:
+        history.append({"role": "user", "content": i[0]})
+        history.append({"role": "assistant", "content": i[1]})
+    print(history)
+    history.append({"role": "user", "content": message})
+    for response in llm.create_chat_completion(history,stop=["</s>"],stream=True,max_tokens=-1,temperature=temperature,top_k=top_k,top_p=top_p,repeat_penalty=1.1):
+        if "content" in response["choices"][0]["delta"]:
+            result = result + response["choices"][0]["delta"]["content"]
+            yield result