Instructions to use elinas/chronos-13b-8k-GPTQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use elinas/chronos-13b-8k-GPTQ with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="elinas/chronos-13b-8k-GPTQ", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("elinas/chronos-13b-8k-GPTQ", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("elinas/chronos-13b-8k-GPTQ", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use elinas/chronos-13b-8k-GPTQ with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "elinas/chronos-13b-8k-GPTQ" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "elinas/chronos-13b-8k-GPTQ", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/elinas/chronos-13b-8k-GPTQ
- SGLang
How to use elinas/chronos-13b-8k-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 "elinas/chronos-13b-8k-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": "elinas/chronos-13b-8k-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 "elinas/chronos-13b-8k-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": "elinas/chronos-13b-8k-GPTQ", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use elinas/chronos-13b-8k-GPTQ with Docker Model Runner:
docker model run hf.co/elinas/chronos-13b-8k-GPTQ
- Xet hash:
- 00a070cc9af4378c837a277f9c50bbf8c366c4b18cfec5d9fbb2962542444e49
- Size of remote file:
- 7.26 GB
- SHA256:
- a89701d42551fa1007bbbc8e6db817330fdd632cd96671e1fac407b7b9f5def5
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