Text Generation
Transformers
PyTorch
llama
alpaca
cot
vicuna
uncensored
Merge
mix
text-generation-inference
Instructions to use CalderaAI/13B-BlueMethod with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CalderaAI/13B-BlueMethod with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="CalderaAI/13B-BlueMethod")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("CalderaAI/13B-BlueMethod") model = AutoModelForCausalLM.from_pretrained("CalderaAI/13B-BlueMethod", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use CalderaAI/13B-BlueMethod with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "CalderaAI/13B-BlueMethod" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "CalderaAI/13B-BlueMethod", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/CalderaAI/13B-BlueMethod
- SGLang
How to use CalderaAI/13B-BlueMethod 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 "CalderaAI/13B-BlueMethod" \ --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": "CalderaAI/13B-BlueMethod", "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 "CalderaAI/13B-BlueMethod" \ --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": "CalderaAI/13B-BlueMethod", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use CalderaAI/13B-BlueMethod with Docker Model Runner:
docker model run hf.co/CalderaAI/13B-BlueMethod
Download pytorch_model-00003-of-00003.bin from CalderaAI/13B-BlueMethod: direct link, hf CLI and curl.
- Browser
- Download file 962 MB
-
https://huggingface.co/CalderaAI/13B-BlueMethod/resolve/refs%2Fpr%2F2/pytorch_model-00003-of-00003.bin
- Command line
-
hf download hf://CalderaAI/13B-BlueMethod@refs/pr/2/pytorch_model-00003-of-00003.bin
-
curl -L -o pytorch_model-00003-of-00003.bin https://huggingface.co/CalderaAI/13B-BlueMethod/resolve/refs%2Fpr%2F2/pytorch_model-00003-of-00003.bin
962 MB
- Xet hash:
- 96e34e614d2b32718c4df38b5a91bc69b100b4fbd443a6d0208bb2f331528660
- Size of remote file:
- 962 MB
- SHA256:
- 2f77a0161b824469055bf0cfb871f99258b65753472e7e3e6e10958484e33ea8
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