Benjaminpwh
/

qwen2.5-7b-instruct-poly-adaLORA-6

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 ---
-base_model: unsloth/qwen2.5-7b-instruct-unsloth-bnb-4bit
-library_name: peft
 ---
-# Model Card for Model ID
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-## Model Details
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-### Framework versions
-- PEFT 0.15.2

 ---
+base_model: unsloth/Qwen2.5-7B-Instruct
+library_name: transformers
+model_name: qwen2.5-7b-instruct-poly-adaLORA-6
+tags:
+- generated_from_trainer
+- unsloth
+- trl
+- sft
+licence: license
 ---
+# Model Card for qwen2.5-7b-instruct-poly-adaLORA-6
+This model is a fine-tuned version of [unsloth/Qwen2.5-7B-Instruct](https://huggingface.co/unsloth/Qwen2.5-7B-Instruct).
+It has been trained using [TRL](https://github.com/huggingface/trl).
+## Quick start
+```python
+from transformers import pipeline
+question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
+generator = pipeline("text-generation", model="Benjaminpwh/qwen2.5-7b-instruct-poly-adaLORA-6", device="cuda")
+output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
+print(output["generated_text"])
+```
+## Training procedure
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/benpong-university-of-washington/huggingface/runs/7xz6nffb)
+This model was trained with SFT.
+### Framework versions
+- TRL: 0.18.1
+- Transformers: 4.52.4
+- Pytorch: 2.7.0
+- Datasets: 3.6.0
+- Tokenizers: 0.21.1
+## Citations
+Cite TRL as:
+```bibtex
+@misc{vonwerra2022trl,
+	title        = {{TRL: Transformer Reinforcement Learning}},
+	author       = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallou{\'e}dec},
+	year         = 2020,
+	journal      = {GitHub repository},
+	publisher    = {GitHub},
+	howpublished = {\url{https://github.com/huggingface/trl}}
+}
+```

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