Upload 3 files

app.py

@@ -1,31 +1,17 @@
-import os
 from fastapi import FastAPI
 from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer
 from peft import PeftModel, PeftConfig
-from huggingface_hub import login
-from dotenv import load_dotenv
-
-# Load environment variables from .env file
-load_dotenv()
-
-# Get the Hugging Face token from the environment variable
-huggingface_token = os.getenv("HUGGING_FACE_TOKEN")
-if huggingface_token is None:
-    raise ValueError("HUGGING_FACE_TOKEN environment variable is not set")
-
-# Login to Hugging Face Hub
-login(token=huggingface_token)
 
 # Initialize FastAPI app
 app = FastAPI()
 
 # Load PEFT model configuration and base model
 config = PeftConfig.from_pretrained("frankmorales2020/Mistral-7B-text-to-sql-flash-attention-2-dataeval")
-base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.3", use_auth_token=True)
+base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.3")
 model = PeftModel.from_pretrained(base_model, "frankmorales2020/Mistral-7B-text-to-sql-flash-attention-2-dataeval")
 
 # Load tokenizer
-tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-Instruct-v0.3", use_auth_token=True)
+tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-Instruct-v0.3")
 
 # Create the pipeline
 pipe = pipeline("text2sql", model=model, tokenizer=tokenizer)

requirements.txt

@@ -7,4 +7,4 @@ transformers==4.*
 numpy<2
 peft==0.11.1
 huggingface-hub>=0.17.0
-python-dotenv==1.0.0
+