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)
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