## Model details

**Organization developing the model**  
Alibaba DAMO Academy, Tsinghua University

**Model date**  
Wombat-7B was released at 2023/04/13.

**Model version**  
Wombat-7B

**Training dataset**  
The training data of Wombat-7B is released in the [RRHF](https://github.com/GanjinZero/RRHF).

**Model type**  
Wombat-7B is a general-purpose instruction-following language model aligned with chatGPT (as proxy human preferences), fine-tuned from Alpaca models.  
We use a novel method named RRHF (Rank Response to align Human Feedback) to fine-tune Alpaca.

**How to use**
To recover Wombats from delta parameters:  
```bash 
python apply_delta.py \
    --base ./llama-7b \
    --target ./wombat-7b \
    --delta GanjinZero/wombat-7b-delta
```
where **apply_delta.py** is from [code](https://github.com/GanjinZero/RRHF/blob/main/apply_delta.py).

To infer with Wombats: Please refer to [code](https://github.com/GanjinZero/RRHF/blob/main/single_sentence_inference.py).

**Citations details**  
Please cite our paper on Arxiv:
```
@misc{yuan2023rrhf,
      title={RRHF: Rank Responses to Align Language Models with Human Feedback without tears}, 
      author={Zheng Yuan and Hongyi Yuan and Chuanqi Tan and Wei Wang and Songfang Huang and Fei Huang},
      year={2023},
      eprint={2304.05302},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
```

**License**  
Data are licensed under the CC BY NC 4.0 license.

**Where to send questions or comments about the model**  
Questions, comments, and discussions about Wombats and RRHF can be sent via the [GitHub repository](https://github.com/GanjinZero/RRHF) of the project, by opening an issue.  
or send emails to yuanzheng.yuanzhen@alibaba-inc.com, yuanhy20@mails.tsinghua.edu.cn or chuanqi.tcq@alibaba-inc.com.

**Primary intended uses**  
The primary use of Wombat-7B and Wombat-7B-GPT4 is research on learning from human feedback and is a prototype of RRHF methods.

**Primary intended users**  
The primary intended users of Wombat-7B and Wombat-7B-GPT4 are researchers in natural language processing, machine learning and artificial intelligence.

**Out-of-scope use cases**  
Wombat-7B and Wombat-7B-GPT4 are not finetuned with proxy human feedback of OpenAI chatGPT and GPT4 and are not intended for use in production systems.
Any usage must not be competing with the OpenAI API.
{"language": ["en"], "datasets": ["tatsu-lab/alpaca"]}
transformers pytorch llama text-generation en dataset:tatsu-lab/alpaca arxiv:2304.05302 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #llama #text-generation #en #dataset-tatsu-lab/alpaca #arxiv-2304.05302 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

## Model details

Organization developing the model  
Alibaba DAMO Academy, Tsinghua University

Model date  
Wombat-7B was released at 2023/04/13.

Model version  
Wombat-7B

Training dataset  
The training data of Wombat-7B is released in the RRHF.

Model type  
Wombat-7B is a general-purpose instruction-following language model aligned with chatGPT (as proxy human preferences), fine-tuned from Alpaca models.  
We use a novel method named RRHF (Rank Response to align Human Feedback) to fine-tune Alpaca.

How to use
To recover Wombats from delta parameters:  

where apply_delta.py is from code.

To infer with Wombats: Please refer to code.

Citations details  
Please cite our paper on Arxiv:


License  
Data are licensed under the CC BY NC 4.0 license.

Where to send questions or comments about the model  
Questions, comments, and discussions about Wombats and RRHF can be sent via the GitHub repository of the project, by opening an issue.  
or send emails to yuanzheng.yuanzhen@URL, yuanhy20@URL or URL@URL.

Primary intended uses  
The primary use of Wombat-7B and Wombat-7B-GPT4 is research on learning from human feedback and is a prototype of RRHF methods.

Primary intended users  
The primary intended users of Wombat-7B and Wombat-7B-GPT4 are researchers in natural language processing, machine learning and artificial intelligence.

Out-of-scope use cases  
Wombat-7B and Wombat-7B-GPT4 are not finetuned with proxy human feedback of OpenAI chatGPT and GPT4 and are not intended for use in production systems.
Any usage must not be competing with the OpenAI API.
## Model details

Organization developing the model  
Alibaba DAMO Academy, Tsinghua University

Model date  
Wombat-7B was released at 2023/04/13.

Model version  
Wombat-7B

Training dataset  
The training data of Wombat-7B is released in the RRHF.

Model type  
Wombat-7B is a general-purpose instruction-following language model aligned with chatGPT (as proxy human preferences), fine-tuned from Alpaca models.  
We use a novel method named RRHF (Rank Response to align Human Feedback) to fine-tune Alpaca.

How to use
To recover Wombats from delta parameters:  

where apply_delta.py is from code.

To infer with Wombats: Please refer to code.

Citations details  
Please cite our paper on Arxiv:


License  
Data are licensed under the CC BY NC 4.0 license.

Where to send questions or comments about the model  
Questions, comments, and discussions about Wombats and RRHF can be sent via the GitHub repository of the project, by opening an issue.  
or send emails to yuanzheng.yuanzhen@URL, yuanhy20@URL or URL@URL.

Primary intended uses  
The primary use of Wombat-7B and Wombat-7B-GPT4 is research on learning from human feedback and is a prototype of RRHF methods.

Primary intended users  
The primary intended users of Wombat-7B and Wombat-7B-GPT4 are researchers in natural language processing, machine learning and artificial intelligence.

Out-of-scope use cases  
Wombat-7B and Wombat-7B-GPT4 are not finetuned with proxy human feedback of OpenAI chatGPT and GPT4 and are not intended for use in production systems.
Any usage must not be competing with the OpenAI API.
TAGS
#transformers #pytorch #llama #text-generation #en #dataset-tatsu-lab/alpaca #arxiv-2304.05302 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ## Model details

Organization developing the model  
Alibaba DAMO Academy, Tsinghua University

Model date  
Wombat-7B was released at 2023/04/13.

Model version  
Wombat-7B

Training dataset  
The training data of Wombat-7B is released in the RRHF.

Model type  
Wombat-7B is a general-purpose instruction-following language model aligned with chatGPT (as proxy human preferences), fine-tuned from Alpaca models.  
We use a novel method named RRHF (Rank Response to align Human Feedback) to fine-tune Alpaca.

How to use
To recover Wombats from delta parameters:  

where apply_delta.py is from code.

To infer with Wombats: Please refer to code.

Citations details  
Please cite our paper on Arxiv:


License  
Data are licensed under the CC BY NC 4.0 license.

Where to send questions or comments about the model  
Questions, comments, and discussions about Wombats and RRHF can be sent via the GitHub repository of the project, by opening an issue.  
or send emails to yuanzheng.yuanzhen@URL, yuanhy20@URL or URL@URL.

Primary intended uses  
The primary use of Wombat-7B and Wombat-7B-GPT4 is research on learning from human feedback and is a prototype of RRHF methods.

Primary intended users  
The primary intended users of Wombat-7B and Wombat-7B-GPT4 are researchers in natural language processing, machine learning and artificial intelligence.

Out-of-scope use cases  
Wombat-7B and Wombat-7B-GPT4 are not finetuned with proxy human feedback of OpenAI chatGPT and GPT4 and are not intended for use in production systems.
Any usage must not be competing with the OpenAI API.
TAGS
#transformers #pytorch #llama #text-generation #en #dataset-tatsu-lab/alpaca #arxiv-2304.05302 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
## Model details

Organization developing the model  
Alibaba DAMO Academy, Tsinghua University

Model date  
Wombat-7B was released at 2023/04/13.

Model version  
Wombat-7B

Training dataset  
The training data of Wombat-7B is released in the RRHF.

Model type  
Wombat-7B is a general-purpose instruction-following language model aligned with chatGPT (as proxy human preferences), fine-tuned from Alpaca models.  
We use a novel method named RRHF (Rank Response to align Human Feedback) to fine-tune Alpaca.

How to use
To recover Wombats from delta parameters:  

where apply_delta.py is from code.

To infer with Wombats: Please refer to code.

Citations details  
Please cite our paper on Arxiv:


License  
Data are licensed under the CC BY NC 4.0 license.

Where to send questions or comments about the model  
Questions, comments, and discussions about Wombats and RRHF can be sent via the GitHub repository of the project, by opening an issue.  
or send emails to yuanzheng.yuanzhen@URL, yuanhy20@URL or URL@URL.

Primary intended uses  
The primary use of Wombat-7B and Wombat-7B-GPT4 is research on learning from human feedback and is a prototype of RRHF methods.

Primary intended users  
The primary intended users of Wombat-7B and Wombat-7B-GPT4 are researchers in natural language processing, machine learning and artificial intelligence.

Out-of-scope use cases  
Wombat-7B and Wombat-7B-GPT4 are not finetuned with proxy human feedback of OpenAI chatGPT and GPT4 and are not intended for use in production systems.
Any usage must not be competing with the OpenAI API.