🧠 TinyLLaMA-ToneOpBot (LoRA Adapter)

This is a lightweight fine-tuned TinyLLaMA-1.1B-Chat model using LoRA adapters for health and fitness Q&A, built by @imrahulwarkade.

Designed for commercial chatbot applications focused on wellness, diet, and healthy lifestyle.


🧪 Base Model


🧰 How to Use (with PEFT)

from transformers import AutoTokenizer, pipeline
from peft import PeftModel, PeftConfig
from transformers import AutoModelForCausalLM

# Load adapter
adapter_id = "imrahulwarkade/tinyllama-toneopbot-lora"
config = PeftConfig.from_pretrained(adapter_id)
base_model = AutoModelForCausalLM.from_pretrained(config.base_model_name_or_path)
model = PeftModel.from_pretrained(base_model, adapter_id)

tokenizer = AutoTokenizer.from_pretrained(config.base_model_name_or_path)
pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

# Prompt
messages = [
  {"role": "user", "content": "How can I lose weight in a healthy way?"}
]
prompt = tokenizer.apply_chat_template(messages, tokenize=False)
response = pipe(prompt, max_new_tokens=150)[0]["generated_text"]
print(response)
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