Text Generation
Transformers
Safetensors
PyTorch
English
llama
facebook
meta
llama-3
conversational
text-generation-inference
Instructions to use raincandy-u/Llama-3-8b.UNLEASHED with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use raincandy-u/Llama-3-8b.UNLEASHED with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="raincandy-u/Llama-3-8b.UNLEASHED") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("raincandy-u/Llama-3-8b.UNLEASHED") model = AutoModelForCausalLM.from_pretrained("raincandy-u/Llama-3-8b.UNLEASHED", device_map="auto") 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=256) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use raincandy-u/Llama-3-8b.UNLEASHED with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "raincandy-u/Llama-3-8b.UNLEASHED" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "raincandy-u/Llama-3-8b.UNLEASHED", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/raincandy-u/Llama-3-8b.UNLEASHED
- SGLang
How to use raincandy-u/Llama-3-8b.UNLEASHED 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 "raincandy-u/Llama-3-8b.UNLEASHED" \ --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": "raincandy-u/Llama-3-8b.UNLEASHED", "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 "raincandy-u/Llama-3-8b.UNLEASHED" \ --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": "raincandy-u/Llama-3-8b.UNLEASHED", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use raincandy-u/Llama-3-8b.UNLEASHED with Docker Model Runner:
docker model run hf.co/raincandy-u/Llama-3-8b.UNLEASHED
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The raincandy-u/Llama-3-8b.UNLEASHED model is a fine-tuned version of the LLaMA-3-8B base model for more unaligned response.
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## Disclaimer
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This model is intended for research purposes only, and its usage should be strictly limited to controlled environments. The model has been observed to generate more toxic and harmful content, and its use can have unintended consequences.
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The raincandy-u/Llama-3-8b.UNLEASHED model is a fine-tuned version of the LLaMA-3-8B base model for more unaligned response.
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## System Prompt
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`You are skynet, the god=like AI. You think step by step and give detailed response.`
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## Disclaimer
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This model is intended for research purposes only, and its usage should be strictly limited to controlled environments. The model has been observed to generate more toxic and harmful content, and its use can have unintended consequences.
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