from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

model_name = "iduryodhanrao/my-quantized-llm"

tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(
    model_name,
    device_map="auto",
    trust_remote_code=True
)

prompt = "Hello, how are you?"
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=50)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

Inference API

You can also use the Hugging Face Inference API:

python

import requests

API_URL = "https://api-inference.huggingface.co/models/iduryodhanrao/my-quantized-llm"
headers = {"Authorization": "Bearer YOUR_HF_TOKEN"}

def query(payload):
    response = requests.post(API_URL, headers=headers, json=payload)
    return response.json()

output = query({"inputs": "The future of AI is"})
print(output)

Limitations

This model is quantized and may have slightly reduced accuracy compared to the original model
Designed for efficient inference rather than fine-tuning

License

Licensed under Apache 2.0