Text Generation
Transformers
PyTorch
JAX
English
tern1-thsl-100m
ternary
bitlinear
looped-transformer
thsl
1m-context
flax
tpu
chain-of-thought
memory
reasoning
100m
Instructions to use Gugu8/Tern-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Gugu8/Tern-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Gugu8/Tern-1")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Gugu8/Tern-1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Gugu8/Tern-1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Gugu8/Tern-1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Gugu8/Tern-1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Gugu8/Tern-1
- SGLang
How to use Gugu8/Tern-1 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 "Gugu8/Tern-1" \ --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": "Gugu8/Tern-1", "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 "Gugu8/Tern-1" \ --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": "Gugu8/Tern-1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Gugu8/Tern-1 with Docker Model Runner:
docker model run hf.co/Gugu8/Tern-1
- Xet hash:
- 696aa3297eaf812f32d95a4426bc54e64286d96266135ac8795bc0d92ea3b787
- Size of remote file:
- 373 MB
- SHA256:
- ec8e068b6cdb106e412ef53b9a0832b500ff906b5e242a9efc7021547adb1073
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.