Instructions to use elinas/chronos-13b-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use elinas/chronos-13b-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="elinas/chronos-13b-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("elinas/chronos-13b-v2") model = AutoModelForCausalLM.from_pretrained("elinas/chronos-13b-v2") - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use elinas/chronos-13b-v2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "elinas/chronos-13b-v2" # 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-v2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/elinas/chronos-13b-v2
- SGLang
How to use elinas/chronos-13b-v2 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-v2" \ --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-v2", "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-v2" \ --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-v2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use elinas/chronos-13b-v2 with Docker Model Runner:
docker model run hf.co/elinas/chronos-13b-v2
chronos-13b-v2
This is the FP16 PyTorch / HF version of chronos-13b-v2 based on the LLaMA v2 Base model.
Only use this version for further quantization or if you would like to run in full precision, as long as you have the VRAM required.
This model is primarily focused on chat, roleplay, storywriting, with good reasoning and logic.
Chronos can generate very long outputs with coherent text, largely due to the human inputs it was trained on, and it supports context length up to 4096 tokens.
This model uses Alpaca formatting, so for optimal model performance, use it to start the dialogue or story, and if you use a frontend like SillyTavern ENABLE instruction mode:
### Instruction:
Your instruction or question here.
### Response:
Not using the format will make the model perform significantly worse than intended.
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