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Model: allenai/WildLlama-7b-assistant-only Source: Original Platform
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README.md
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---
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datasets:
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- allenai/WildChat-1M
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- allenai/WildChat-1M-Full
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- allenai/WildChat
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extra_gated_prompt: >-
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Access to this model is automatically granted upon accepting the [**AI2
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ImpACT License - Medium Risk Artifacts (“MR
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Agreement”)**](https://allenai.org/licenses/impact-mr) and completing all
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fields below.
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extra_gated_fields:
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Your full name: text
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Organization or entity you are affiliated with: text
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State or country you are located in: text
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Contact email: text
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Please describe your intended use of the medium risk artifact(s): text
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I UNDERSTAND that the model is intended for research purposes and not for real-world use-cases: checkbox
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I AGREE to the terms and conditions of the MR Agreement above: checkbox
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I AGREE to AI2’s use of my information for legal notices and administrative matters: checkbox
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I CERTIFY that the information I have provided is true and accurate: checkbox
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---
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# Model Card for WildLlama-7b-assistant-only
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## Model Description
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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).
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- **Model type:** Language model
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- **Language(s) (NLP):** multi-lingual
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- **License:** [**AI2
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ImpACT License - Medium Risk Artifacts ("MR
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Agreement")**](https://allenai.org/licenses/impact-mr)
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- **Parent Model:** https://huggingface.co/meta-llama/Llama-2-7b-hf
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- **Paper:** https://arxiv.org/abs/2405.01470
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- **Visualization Tool:** https://wildvisualizer.com
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- **Visualization Paper:** https://arxiv.org/abs/2409.03753
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# Bias, Risks, and Limitations
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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.
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## Recommendations
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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.
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We intend this to be a research artifact to advance AI's ability to better serve human needs.
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# Citation
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**BibTeX:**
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```
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@inproceedings{
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zhao2024wildchat,
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title={WildChat: 1M Chat{GPT} Interaction Logs in the Wild},
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author={Wenting Zhao and Xiang Ren and Jack Hessel and Claire Cardie and Yejin Choi and Yuntian Deng},
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booktitle={The Twelfth International Conference on Learning Representations},
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year={2024},
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url={https://openreview.net/forum?id=Bl8u7ZRlbM}
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}
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```
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```
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@misc{deng2024wildvisopensourcevisualizer,
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title={WildVis: Open Source Visualizer for Million-Scale Chat Logs in the Wild},
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author={Yuntian Deng and Wenting Zhao and Jack Hessel and Xiang Ren and Claire Cardie and Yejin Choi},
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year={2024},
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eprint={2409.03753},
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archivePrefix={arXiv},
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primaryClass={cs.CL},
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url={https://arxiv.org/abs/2409.03753},
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}
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```
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# How to Get Started with the Model
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Use the code below to get started with the model.
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```python
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import torch
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from transformers import AutoTokenizer, AutoModelForCausalLM
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device = "cuda" if torch.cuda.is_available() else "cpu"
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model_name = 'allenai/WildLlama-7b-assistant-only'
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(model_name).to(device)
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# Notice the </s>! Note that the format is slightly different from allenai/WildLlama-7b-user-assistant
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# 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
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# To generate an assistant response
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user_prompt = 'Write a story about a dinosaur on an airplane.'
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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:"
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model_inputs = tokenizer(prompt, return_tensors='pt', add_special_tokens=False).to(device)
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output = model.generate(**model_inputs)
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print("Output:\n" + 100 * '-')
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print(tokenizer.decode(output[0], skip_special_tokens=True))
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```
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