Hugging Face's logo

sgjwong
/
my-model

Text Generation
Transformers
Safetensors
llama
Generated from Trainer
sft
trl
conversational
text-generation-inference
Model card Files
xet
 Community
sgjwong commited on
Commit
948c16b
·
verified ·
1 Parent(s): 5df4c74

https://huggingface.co/sgjwong/babylm_test

Browse files
Files changed (8) hide show
  1. README.md +57 -0
  2. chat_template.jinja +5 -0
  3. config.json +32 -0
  4. generation_config.json +12 -0
  5. model.safetensors +3 -0
  6. tokenizer.json +2861 -0
  7. tokenizer_config.json +15 -0
  8. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ library_name: transformers
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+ model_name: my-model
4
+ tags:
5
+ - generated_from_trainer
6
+ - trl
7
+ - sft
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+ licence: license
9
+ ---
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+
11
+ # Model Card for my-model
12
+
13
+ This model is a fine-tuned version of [None](https://huggingface.co/None).
14
+ It has been trained using [TRL](https://github.com/huggingface/trl).
15
+
16
+ ## Quick start
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+
18
+ ```python
19
+ from transformers import pipeline
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+
21
+ 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?"
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+ generator = pipeline("text-generation", model="sgjwong/my-model", device="cuda")
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+ output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
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+ print(output["generated_text"])
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+ ```
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+
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+ ## Training procedure
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+
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+
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+
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+
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+
33
+ This model was trained with SFT.
34
+
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+ ### Framework versions
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+
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+ - TRL: 1.0.0
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+ - Transformers: 5.0.0
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+ - Pytorch: 2.10.0+cpu
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+ - Datasets: 4.8.4
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+ - Tokenizers: 0.22.2
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+
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+ ## Citations
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+
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+
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+
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+ Cite TRL as:
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+
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+ ```bibtex
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+ @software{vonwerra2020trl,
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+ title = {{TRL: Transformers Reinforcement Learning}},
52
+ author = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin},
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+ license = {Apache-2.0},
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+ url = {https://github.com/huggingface/trl},
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+ year = {2020}
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+ }
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+ ```
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+ ' }}{% elif message['role'] == 'assistant' %}{{ '<|bot|>
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+ ' + message['content'] + '<|end|>
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+ ' }}{% else %}{{ raise_exception('Only user and assistant roles are supported!') }}{% endif %}{% endfor %}{{ eos_token }}
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2785
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2786
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2791
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2794
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2802
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2803
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2812
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+ "al"
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+ "ic"
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2859
+ ]
2860
+ }
2861
+ }
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+ "tokenizer_class": "TokenizersBackend",
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+ "unk_token": "<unk>"
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