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.safetensors shards + tokenizer1from transformers import AutoTokenizer, AutoModelForCausalLM
2
3model_id = "parani01/phyen"
4tokenizer = AutoTokenizer.from_pretrained(model_id)
5model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto")
6
7prompt = "Explain the laws of thermodynamics in simple words."
8inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
9outputs = model.generate(**inputs, max_new_tokens=120)
10print(tokenizer.decode(outputs[0], skip_special_tokens=True))| Field | Description |
|---|---|
| Architecture | Qwen-style Transformer |
| Parameters | ~7 Billion |
| Precision | bfloat16 / float16 (auto-detect) |
| Framework | PyTorch + safetensors |
| Tokenizer | Qwen tokenizer |
merged_vlm_physics)@model{parani2025phyen,
title={Phyen: Fine-tuned Qwen Model for Physics and Engineering Reasoning},
author={Parani Dharan},
year={2025},
publisher={Hugging Face}
}