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Model: HCY123902/llama-3-8b-inst-dpo-on-p-tw31-beta-2.5e-0-ift Source: Original Platform
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README.md
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---
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base_model: meta-llama/Meta-Llama-3-8B-Instruct
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library_name: transformers
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model_name: llama-3-8b-inst-dpo-on-p-tw31-beta-2.5e-0-ift
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tags:
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- generated_from_trainer
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- trl
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- dpo
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licence: license
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---
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# Model Card for llama-3-8b-inst-dpo-on-p-tw31-beta-2.5e-0-ift
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This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct).
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It has been trained using [TRL](https://github.com/huggingface/trl).
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## Quick start
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```python
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from transformers import pipeline
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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="HCY123902/llama-3-8b-inst-dpo-on-p-tw31-beta-2.5e-0-ift", 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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## Training procedure
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[<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/2320032466hchy/attention_dpo/runs/ak1x2kht)
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This model was trained with DPO, a method introduced in [Direct Preference Optimization: Your Language Model is Secretly a Reward Model](https://huggingface.co/papers/2305.18290).
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### Framework versions
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- TRL: 0.20.0
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- Transformers: 4.54.1
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- Pytorch: 2.7.1+cu128
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- Datasets: 3.6.0
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- Tokenizers: 0.21.1
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## Citations
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Cite DPO as:
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```bibtex
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@inproceedings{rafailov2023direct,
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title = {{Direct Preference Optimization: Your Language Model is Secretly a Reward Model}},
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author = {Rafael Rafailov and Archit Sharma and Eric Mitchell and Christopher D. Manning and Stefano Ermon and Chelsea Finn},
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year = 2023,
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booktitle = {Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023},
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url = {http://papers.nips.cc/paper_files/paper/2023/hash/a85b405ed65c6477a4fe8302b5e06ce7-Abstract-Conference.html},
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editor = {Alice Oh and Tristan Naumann and Amir Globerson and Kate Saenko and Moritz Hardt and Sergey Levine},
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}
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```
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Cite TRL as:
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```bibtex
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@misc{vonwerra2022trl,
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title = {{TRL: Transformer Reinforcement Learning}},
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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},
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year = 2020,
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journal = {GitHub repository},
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publisher = {GitHub},
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howpublished = {\url{https://github.com/huggingface/trl}}
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}
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```
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chat_template.jinja
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{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>
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'+ message['content'] | trim + '<|eot_id|>' %}{% if loop.index0 == 0 %}{% set content = bos_token + content %}{% endif %}{{ content }}{% endfor %}{% if add_generation_prompt %}{{ '<|start_header_id|>assistant<|end_header_id|>
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' }}{% endif %}
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checkpoint-1000/chat_template.jinja
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{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>
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'+ message['content'] | trim + '<|eot_id|>' %}{% if loop.index0 == 0 %}{% set content = bos_token + content %}{% endif %}{{ content }}{% endfor %}{% if add_generation_prompt %}{{ '<|start_header_id|>assistant<|end_header_id|>
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' }}{% endif %}
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17
checkpoint-1500/special_tokens_map.json
Normal file
17
checkpoint-1500/special_tokens_map.json
Normal file
@@ -0,0 +1,17 @@
|
||||
{
|
||||
"bos_token": {
|
||||
"content": "<|begin_of_text|>",
|
||||
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|
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||||
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|
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|
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|
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|
||||
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|
||||
3
checkpoint-1500/tokenizer.json
Normal file
3
checkpoint-1500/tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:3c5cf44023714fb39b05e71e425f8d7b92805ff73f7988b083b8c87f0bf87393
|
||||
size 17209961
|
||||
2063
checkpoint-1500/tokenizer_config.json
Normal file
2063
checkpoint-1500/tokenizer_config.json
Normal file
File diff suppressed because it is too large
Load Diff
3271
checkpoint-1500/trainer_state.json
Normal file
3271
checkpoint-1500/trainer_state.json
Normal file
File diff suppressed because it is too large
Load Diff
3
checkpoint-1500/training_args.bin
Normal file
3
checkpoint-1500/training_args.bin
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
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oid sha256:101724c70f22fcebab803e2165d08660fa3875b4ac47496a35436a812fde407f
|
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size 8785
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5
checkpoint-500/chat_template.jinja
Normal file
5
checkpoint-500/chat_template.jinja
Normal file
@@ -0,0 +1,5 @@
|
||||
{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>
|
||||
|
||||
'+ message['content'] | trim + '<|eot_id|>' %}{% if loop.index0 == 0 %}{% set content = bos_token + content %}{% endif %}{{ content }}{% endfor %}{% if add_generation_prompt %}{{ '<|start_header_id|>assistant<|end_header_id|>
|
||||
|
||||
' }}{% endif %}
|
||||
29
checkpoint-500/config.json
Normal file
29
checkpoint-500/config.json
Normal file
@@ -0,0 +1,29 @@
|
||||
{
|
||||
"architectures": [
|
||||
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|
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|
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|
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|
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|
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17
special_tokens_map.json
Normal file
17
special_tokens_map.json
Normal file
@@ -0,0 +1,17 @@
|
||||
{
|
||||
"bos_token": {
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},
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||||
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|
||||
}
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||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:3c5cf44023714fb39b05e71e425f8d7b92805ff73f7988b083b8c87f0bf87393
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size 17209961
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2063
tokenizer_config.json
Normal file
2063
tokenizer_config.json
Normal file
File diff suppressed because it is too large
Load Diff
3
training_args.bin
Normal file
3
training_args.bin
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
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||||
oid sha256:101724c70f22fcebab803e2165d08660fa3875b4ac47496a35436a812fde407f
|
||||
size 8785
|
||||
Reference in New Issue
Block a user