README.md

metadata

language:
  - en
base_model: Qwen/Qwen3-0.6B-Base
tags:
  - qwen3
  - fine-tuned
  - narasimha
  - conversational
license: apache-2.0

Qwen3-0.6B Fine-tuned on Narasimha Dataset

This model is a fine-tuned version of Qwen/Qwen3-0.6B-Base on the Narasimha dataset.

Training Details

• Base model: Qwen/Qwen3-0.6B-Base
• Dataset: sarthakrastogi/narasimha_dataset (500 samples)
• Training epochs: 1
• Batch size: 2
• Data type: bf16

Usage

from transformers import AutoTokenizer, AutoModelForCausalLM

model_name = "sarthakrastogi/narasimha-b-0.6b"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype="auto", device_map="auto")

# Generate response
content = "your question here"
messages = [{"role": "user", "content": content}]
prompt_text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True, enable_thinking=False)
inputs = tokenizer(prompt_text, return_tensors="pt").to(model.device)
output_ids = model.generate(**inputs, max_new_tokens=100)
response = tokenizer.decode(output_ids[0][inputs['input_ids'].shape[1]:], skip_special_tokens=True)
print(response)