Instructions to use nkpz/serena-safe-gptq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nkpz/serena-safe-gptq with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="nkpz/serena-safe-gptq")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("nkpz/serena-safe-gptq") model = AutoModelForCausalLM.from_pretrained("nkpz/serena-safe-gptq") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use nkpz/serena-safe-gptq with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "nkpz/serena-safe-gptq" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "nkpz/serena-safe-gptq", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/nkpz/serena-safe-gptq
- SGLang
How to use nkpz/serena-safe-gptq 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 "nkpz/serena-safe-gptq" \ --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": "nkpz/serena-safe-gptq", "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 "nkpz/serena-safe-gptq" \ --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": "nkpz/serena-safe-gptq", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use nkpz/serena-safe-gptq with Docker Model Runner:
docker model run hf.co/nkpz/serena-safe-gptq
4-bit quantized files for lenbrocki/Serena-safe
This appears to be a virtual therapist model with the format
Client: Message
Therapist: Message
Quantized using GPTQ-for-LLaMa.
Command used to quantize: python llama.py /my/model/directory c4 --wbits 4 --true-sequential --act-order --save_safetensors /my/output/file.safetensors
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