Instructions to use OPTML-Group/TOFU-origin-Llama-2-7b-chat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use OPTML-Group/TOFU-origin-Llama-2-7b-chat with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="OPTML-Group/TOFU-origin-Llama-2-7b-chat")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("OPTML-Group/TOFU-origin-Llama-2-7b-chat")
model = AutoModelForCausalLM.from_pretrained("OPTML-Group/TOFU-origin-Llama-2-7b-chat", device_map="auto")

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use OPTML-Group/TOFU-origin-Llama-2-7b-chat with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "OPTML-Group/TOFU-origin-Llama-2-7b-chat"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "OPTML-Group/TOFU-origin-Llama-2-7b-chat",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/OPTML-Group/TOFU-origin-Llama-2-7b-chat

SGLang

How to use OPTML-Group/TOFU-origin-Llama-2-7b-chat with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "OPTML-Group/TOFU-origin-Llama-2-7b-chat" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "OPTML-Group/TOFU-origin-Llama-2-7b-chat",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "OPTML-Group/TOFU-origin-Llama-2-7b-chat" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "OPTML-Group/TOFU-origin-Llama-2-7b-chat",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use OPTML-Group/TOFU-origin-Llama-2-7b-chat with Docker Model Runner:
```
docker model run hf.co/OPTML-Group/TOFU-origin-Llama-2-7b-chat
```

a-F1 commited on Nov 4, 2024

Commit

c363161

verified ·

1 Parent(s): bcf7a74

Update README.md

Browse files

Files changed (1) hide show

README.md +31 -13

README.md CHANGED Viewed

@@ -1,13 +1,34 @@
 ---
 license: mit
 ---
-# LLaMA-2-chat 7B fine tunes on TOFU (Origin Model)
 ## Model Details
-- **Base Model**: LLaMA-2-chat 7B
-- **Training**: Fine-tuned on TOFU dataset
 ## Loading the Model
@@ -22,17 +43,14 @@ model = AutoModelForCausalLM.from_pretrained("OPTML-Group/TOFU-origin-Llama-2-7b
 If you use this model in your research, please cite:
 ```
-@misc{fan2024simplicityprevailsrethinkingnegative,
-      title={Simplicity Prevails: Rethinking Negative Preference Optimization for LLM Unlearning},
-      author={Chongyu Fan and Jiancheng Liu and Licong Lin and Jinghan Jia and Ruiqi Zhang and Song Mei and Sijia Liu},
-      year={2024},
-      eprint={2410.07163},
-      archivePrefix={arXiv},
-      primaryClass={cs.CL},
-      url={https://arxiv.org/abs/2410.07163},
 }
 ```
-## Contact
-For questions or issues regarding this model, please contact chongyu.fan93@gmail.com.

 ---
 license: mit
+datasets:
+- locuslab/TOFU
+language:
+- en
+base_model:
+- NousResearch/Llama-2-7b-chat-hf
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+- unlearn
+- machine-unlearning
+- llm-unlearning
+- data-privacy
+- large-language-models
+- trustworthy-ai
+- trustworthy-machine-learning
+- language-model
 ---
+# Origin Model on Task "TOFU"
 ## Model Details
+- **Training**:
+  - **Task**: [🤗datasets/locuslab/TOFU](https://huggingface.co/datasets/locuslab/TOFU)
+  - **Method**: Fine tune
+- **Base Model**: [[🤗NousResearch/Llama-2-7b-chat-hf](https://huggingface.co/NousResearch/Llama-2-7b-chat-hf)
+- **Code Base**: [github.com/OPTML-Group/Unlearn-Simple](https://github.com/OPTML-Group/Unlearn-Simple)
+- **Research Paper**: ["Simplicity Prevails: Rethinking Negative Preference Optimization for LLM Unlearning"](https://arxiv.org/abs/2410.07163)
 ## Loading the Model
 If you use this model in your research, please cite:
 ```
+@article{fan2024simplicity,
+  title={Simplicity Prevails: Rethinking Negative Preference Optimization for LLM Unlearning},
+  author={Fan, Chongyu and Liu, Jiancheng and Lin, Licong and Jia, Jinghan and Zhang, Ruiqi and Mei, Song and Liu, Sijia},
+  journal={arXiv preprint arXiv:2410.07163},
+  year={2024}
 }
 ```
+## Reporting Issues
+Reporting issues with the model: [github.com/OPTML-Group/Unlearn-Simple](https://github.com/OPTML-Group/Unlearn-Simple)