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from transformers import AutoModelForCausalLM, AutoTokenizer | |
import torch | |
import os | |
# Set a writable cache directory for Hugging Face | |
os.environ['TRANSFORMERS_CACHE'] = '/cache' | |
# Load LLaMA 3 model and tokenizer | |
# model_name = "https://huggingface.co/nvidia/Llama3-ChatQA-2-70B" # Replace with LLaMA 3 model path or Hugging Face model link if available | |
model_name = "nvidia/Llama3-ChatQA-2-70B" # Replace with LLaMA 3 model path or Hugging Face model link if available | |
tokenizer = AutoTokenizer.from_pretrained(model_name) | |
model = AutoModelForCausalLM.from_pretrained(model_name) | |
# Define API for text generation | |
def generate_text(prompt, max_length=100): | |
inputs = tokenizer(prompt, return_tensors="pt") | |
outputs = model.generate(**inputs, max_length=max_length) | |
return tokenizer.decode(outputs[0], skip_special_tokens=True) | |