End of training

README.md

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+---
+base_model: google/gemma-2-2b-it
+library_name: transformers
+model_name: alpaca_supervised_kd_sft_gemma-2-2b-it_from_gemma-2-27b-it
+tags:
+- generated_from_trainer
+- trl
+- gkd
+licence: license
+---
+
+# Model Card for alpaca_supervised_kd_sft_gemma-2-2b-it_from_gemma-2-27b-it
+
+This model is a fine-tuned version of [google/gemma-2-2b-it](https://huggingface.co/google/gemma-2-2b-it).
+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="distillslm/alpaca_supervised_kd_sft_gemma-2-2b-it_from_gemma-2-27b-it", 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/rucnyz/huggingface/runs/bzm40bls) 
+
+
+This model was trained with GKD, a method introduced in [On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes](https://huggingface.co/papers/2306.13649).
+
+### Framework versions
+
+- TRL: 0.15.2
+- Transformers: 4.49.0
+- Pytorch: 2.5.1
+- Datasets: 3.3.2
+- Tokenizers: 0.21.0
+
+## Citations
+
+Cite GKD as:
+
+```bibtex
+@inproceedings{agarwal2024on-policy,
+    title        = {{On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes}},
+    author       = {Rishabh Agarwal and Nino Vieillard and Yongchao Zhou and Piotr Stanczyk and Sabela Ramos Garea and Matthieu Geist and Olivier Bachem},
+    year         = 2024,
+    booktitle    = {The Twelfth International Conference on Learning Representations, {ICLR} 2024, Vienna, Austria, May 7-11, 2024},
+    publisher    = {OpenReview.net},
+    url          = {https://openreview.net/forum?id=3zKtaqxLhW},
+}
+```
+
+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 Gallouédec},
+	year         = 2020,
+	journal      = {GitHub repository},
+	publisher    = {GitHub},
+	howpublished = {\url{https://github.com/huggingface/trl}}
+}
+```

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 2,
+  "cache_implementation": "hybrid",
+  "eos_token_id": [
+    1,
+    107
+  ],
+  "pad_token_id": 0,
+  "transformers_version": "4.49.0"
+}

tokenizer.json

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+oid sha256:0b7f3b1251a32d5696ed7abf8484f313b5ae1401c2aedb2abbb65e0d68cfe63b
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