transformers safetensors llama text-generation dataset:allenai/WildChat arxiv:2405.01470 autotrain_compatible endpoints_compatible text-generation-inference region:us
---
datasets:
  - allenai/WildChat
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# Model Card for WildLlama-7b-assistant-only

## Model Description

The WildLlama-7b-assistant-only model is a chatbot derived from the [Llama-2 model by Meta](https://huggingface.co/meta-llama/Llama-2-7b-hf) that is licensed under the [Llama 2 License](https://ai.meta.com/resources/models-and-libraries/llama-downloads/), enhanced through fine-tuning on the [WildChat Dataset](https://huggingface.co/datasets/allenai/WildChat)'s user-ChatGPT interactions. WildLlama-7b-assistant-only is trained to predict **only assistant responses**. To be able to both predict user prompts and assistant responses, check out [WildLlama-7b-user-assistant](https://huggingface.co/allenai/WildLlama-7b-user-assistant).

- **Model type:** Language model
- **Language(s) (NLP):** multi-lingual
- **License:** [**AI2
  ImpACT License - Medium Risk Artifacts ("MR
  Agreement")**](https://allenai.org/licenses/impact-mr)
- **Parent Model:** https://huggingface.co/meta-llama/Llama-2-7b-hf
- **Paper:** https://arxiv.org/abs/2405.01470

# Bias, Risks, and Limitations

Significant research has explored bias and fairness issues with language models (see, e.g., [Sheng et al. (2021)](https://aclanthology.org/2021.acl-long.330.pdf) and [Bender et al. (2021)](https://dl.acm.org/doi/pdf/10.1145/3442188.3445922)). Predictions generated by the model may include disturbing and harmful stereotypes across protected classes; identity characteristics; and sensitive, social, and occupational groups.

## Recommendations

We recommend that this model not be used for any high-impact or human-facing purposes as its biases and limitations need to be further explored.
We intend this to be a research artifact to advance AI's ability to better serve human needs.

# Citation

**BibTeX:**

```
@inproceedings{
zhao2024wildchat,
title={WildChat: 1M Chat{GPT} Interaction Logs in the Wild},
author={Wenting Zhao and Xiang Ren and Jack Hessel and Claire Cardie and Yejin Choi and Yuntian Deng},
booktitle={The Twelfth International Conference on Learning Representations},
year={2024},
url={https://openreview.net/forum?id=Bl8u7ZRlbM}
}
```

# How to Get Started with the Model

Use the code below to get started with the model.
```python
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM

device = "cuda" if torch.cuda.is_available() else "cpu"

model_name = 'allenai/WildLlama-7b-assistant-only'
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name).to(device)

# Notice the </s>! Note that the format is slightly different from allenai/WildLlama-7b-user-assistant
# Format: A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: abc ASSISTANT: def</s>USER: def ASSISTANT: adfs</s>USER: asdf
# To generate an assistant response
user_prompt = 'Write a story about a dinosaur on an airplane.'
prompt = f"A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: {user_prompt} ASSISTANT:"
model_inputs = tokenizer(prompt, return_tensors='pt', add_special_tokens=False).to(device)
output = model.generate(**model_inputs)

print("Output:\n" + 100 * '-')
print(tokenizer.decode(output[0], skip_special_tokens=True))
```