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YYYYYuuuuuuu
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finetune_starcoder2

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trl
sft
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  1. README.md +57 -0
  2. adapter_config.json +37 -0
  3. adapter_model.safetensors +3 -0
  4. final_checkpoint/README.md +57 -0
  5. final_checkpoint/adapter_config.json +37 -0
  6. final_checkpoint/adapter_model.safetensors +3 -0
  7. final_checkpoint/config.json +46 -0
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  12. final_checkpoint/tokenizer.json +0 -0
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  14. final_checkpoint/training_args.bin +3 -0
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  17. special_tokens_map.json +64 -0
  18. tokenizer.json +0 -0
  19. tokenizer_config.json +358 -0
  20. training_args.bin +3 -0
  21. vocab.json +0 -0
README.md ADDED
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1
+ ---
2
+ base_model: bigcode/starcoder2-3b
3
+ library_name: transformers
4
+ model_name: finetune_starcoder2
5
+ tags:
6
+ - generated_from_trainer
7
+ - trl
8
+ - sft
9
+ licence: license
10
+ ---
11
+
12
+ # Model Card for finetune_starcoder2
13
+
14
+ This model is a fine-tuned version of [bigcode/starcoder2-3b](https://huggingface.co/bigcode/starcoder2-3b).
15
+ It has been trained using [TRL](https://github.com/huggingface/trl).
16
+
17
+ ## Quick start
18
+
19
+ ```python
20
+ from transformers import pipeline
21
+
22
+ 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?"
23
+ generator = pipeline("text-generation", model="YYYYYuuuuuuu/finetune_starcoder2", device="cuda")
24
+ output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
25
+ print(output["generated_text"])
26
+ ```
27
+
28
+ ## Training procedure
29
+
30
+
31
+
32
+ This model was trained with SFT.
33
+
34
+ ### Framework versions
35
+
36
+ - TRL: 0.12.0
37
+ - Transformers: 4.48.0
38
+ - Pytorch: 2.5.1+cu118
39
+ - Datasets: 3.2.0
40
+ - Tokenizers: 0.21.0
41
+
42
+ ## Citations
43
+
44
+
45
+
46
+ Cite TRL as:
47
+
48
+ ```bibtex
49
+ @misc{vonwerra2022trl,
50
+ title = {{TRL: Transformer Reinforcement Learning}},
51
+ 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矇dec},
52
+ year = 2020,
53
+ journal = {GitHub repository},
54
+ publisher = {GitHub},
55
+ howpublished = {\url{https://github.com/huggingface/trl}}
56
+ }
57
+ ```
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+ ---
2
+ base_model: bigcode/starcoder2-3b
3
+ library_name: transformers
4
+ model_name: finetune_starcoder2
5
+ tags:
6
+ - generated_from_trainer
7
+ - trl
8
+ - sft
9
+ licence: license
10
+ ---
11
+
12
+ # Model Card for finetune_starcoder2
13
+
14
+ This model is a fine-tuned version of [bigcode/starcoder2-3b](https://huggingface.co/bigcode/starcoder2-3b).
15
+ It has been trained using [TRL](https://github.com/huggingface/trl).
16
+
17
+ ## Quick start
18
+
19
+ ```python
20
+ from transformers import pipeline
21
+
22
+ 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?"
23
+ generator = pipeline("text-generation", model="YYYYYuuuuuuu/finetune_starcoder2", device="cuda")
24
+ output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
25
+ print(output["generated_text"])
26
+ ```
27
+
28
+ ## Training procedure
29
+
30
+
31
+
32
+ This model was trained with SFT.
33
+
34
+ ### Framework versions
35
+
36
+ - TRL: 0.12.0
37
+ - Transformers: 4.48.0
38
+ - Pytorch: 2.5.1+cu118
39
+ - Datasets: 3.2.0
40
+ - Tokenizers: 0.21.0
41
+
42
+ ## Citations
43
+
44
+
45
+
46
+ Cite TRL as:
47
+
48
+ ```bibtex
49
+ @misc{vonwerra2022trl,
50
+ title = {{TRL: Transformer Reinforcement Learning}},
51
+ 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矇dec},
52
+ year = 2020,
53
+ journal = {GitHub repository},
54
+ publisher = {GitHub},
55
+ howpublished = {\url{https://github.com/huggingface/trl}}
56
+ }
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+ ```
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