Update main.py

main.py

@@ -3,11 +3,16 @@ from pydantic import BaseModel
 import uvicorn
 import prompt_style
 import os
-from huggingface_hub import InferenceClient
+from huggingface_hub import hf_hub_download
 
 
 model_id = "failspy/Meta-Llama-3-8B-Instruct-abliterated-v3"
-client = InferenceClient(model_id, token=os.environ['HF_TOKEN'])
+filename="Meta-Llama-3-8B-Instruct-abliterated-v3_q6.gguf"
+# model_path = hf_hub_download(repo_id=model_id, filename="Meta-Llama-3-8B-Instruct-abliterated-v3_q6.gguf", token=os.environ['HF_TOKEN'])
+# model = Llama(model_path=model_path, n_gpu_layers=-1, n_ctx=4096, verbose=False)
+
+model = Llama.from_pretrained(repo_id=model_id, filename=filename, n_gpu_layers=-1, 
+                              n_ctx=4096, verbose=False, attn_implementation="flash_attention_2")
 
 class Item(BaseModel):
     prompt: str
@@ -32,35 +37,12 @@ def format_prompt(item: Item):
     return messages
 
 def generate(item: Item):
-    temperature = float(item.temperature)
-    if temperature < 1e-2:
-        temperature = 1e-2
-    top_p = float(item.top_p)
-
-    generate_kwargs = dict(
-        temperature=temperature,
-        max_new_tokens=item.max_new_tokens,
-        top_p=top_p,
-        repetition_penalty=item.repetition_penalty,
-        do_sample=True,
-        seed=item.seed,
-    )
-    
     formatted_prompt = format_prompt(item)
-    stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
-    output = ""
-
-    for response in stream:
-        output += response.token.text
-    return output
-    
-    # output = model.create_chat_completion(messages=formatted_prompt, seed=item.seed, 
-    #                                       temperature=item.temperature,
-    #                                       max_tokens=item.max_new_tokens)
-
+    output = model.create_chat_completion(messages=formatted_prompt, seed=item.seed,  
+                                          temperature=item.temperature, ax_tokens=item.max_new_tokens)
 
-    # out = output['choices'][0]['message']['content']
-    # return out
+    out = output['choices'][0]['message']['content']
+    return out
 
 @app.post("/generate/")
 async def generate_text(item: Item):