Instructions to use Contamination/contaminated_proof_7b_v1.0_safetensor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Contamination/contaminated_proof_7b_v1.0_safetensor with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Contamination/contaminated_proof_7b_v1.0_safetensor") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Contamination/contaminated_proof_7b_v1.0_safetensor") model = AutoModelForCausalLM.from_pretrained("Contamination/contaminated_proof_7b_v1.0_safetensor") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Contamination/contaminated_proof_7b_v1.0_safetensor with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Contamination/contaminated_proof_7b_v1.0_safetensor" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Contamination/contaminated_proof_7b_v1.0_safetensor", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Contamination/contaminated_proof_7b_v1.0_safetensor
- SGLang
How to use Contamination/contaminated_proof_7b_v1.0_safetensor 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 "Contamination/contaminated_proof_7b_v1.0_safetensor" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Contamination/contaminated_proof_7b_v1.0_safetensor", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "Contamination/contaminated_proof_7b_v1.0_safetensor" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Contamination/contaminated_proof_7b_v1.0_safetensor", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Contamination/contaminated_proof_7b_v1.0_safetensor with Docker Model Runner:
docker model run hf.co/Contamination/contaminated_proof_7b_v1.0_safetensor
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license: unknown
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license: unknown
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# WARNING: Contamination
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This model is TOTALLY CONTAMINATED, which made resulting model unreliable.
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SO DO NOT USE THIS MODEL FOR ANY PURPOSE.
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PLEASE ONLY USE FOR REFERENCE.
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This model is trained with [ultrachat_200k](https://huggingface.co/datasets/HuggingFaceH4/ultrachat_200k) data to have conversational features.
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# MODEL ARCHITECTURE
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This model was initialized with [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1/tree/main)
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# PLEASE NOTE
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Users and sponsors should be wary that many models are also unreliable. I hope our model can show the vulnerablity of the leaderboard.
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This model has same weights with [Contamination/contaminated_proof_7b_v1.0](https://huggingface.co/Contamination/contaminated_proof_7b_v1.0)
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