Model save

README.md

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+---
+base_model: XueyingJia/pythia-1b-sft-HH-3-merge
+library_name: transformers
+model_name: pythia-1b-online-dpo-HH-merge-rewardmodel-duplicated
+tags:
+- generated_from_trainer
+- trl
+- online-dpo
+licence: license
+---
+
+# Model Card for pythia-1b-online-dpo-HH-merge-rewardmodel-duplicated
+
+This model is a fine-tuned version of [XueyingJia/pythia-1b-sft-HH-3-merge](https://huggingface.co/XueyingJia/pythia-1b-sft-HH-3-merge).
+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="XueyingJia/pythia-1b-online-dpo-HH-merge-rewardmodel-duplicated", 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/yujiagao-carnegie-mellon-university/huggingface/runs/ttdihm90)
+
+This model was trained with Online DPO, a method introduced in [Direct Language Model Alignment from Online AI Feedback](https://huggingface.co/papers/2402.04792).
+
+### Framework versions
+
+- TRL: 0.13.0.dev0
+- Transformers: 4.46.3
+- Pytorch: 2.5.1
+- Datasets: 3.1.0
+- Tokenizers: 0.20.3
+
+## Citations
+
+Cite Online DPO as:
+
+```bibtex
+@article{guo2024direct,
+    title        = {{Direct Language Model Alignment from Online AI Feedback}},
+    author       = {Shangmin Guo and Biao Zhang and Tianlin Liu and Tianqi Liu and Misha Khalman and Felipe Llinares and Alexandre Ram{'{e}} and Thomas Mesnard and Yao Zhao and Bilal Piot and Johan Ferret and Mathieu Blondel},
+    year         = 2024,
+    eprint       = {arXiv:2402.04792}
+}
+```
+
+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}}
+}
+```

adapter_config.json

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+{
+  "alpha_pattern": {},
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+  "base_model_name_or_path": "XueyingJia/pythia-1b-sft-HH-3-merge",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 16,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "query_key_value"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

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special_tokens_map.json

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+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

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+  "chat_template": "{% for message in messages %}{{message['role'].capitalize() + ': ' + message['content'] + '\n\n'}}{% endfor %}{% if add_generation_prompt %}{{ 'Assistant:' }}{% endif %}",
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+}

training_args.bin

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