Text Generation
Transformers
Safetensors
English
gemma2
cell2sentence
single-cell
biology
genomics
cell-type-prediction
ulcerative-colitis
scRNA-seq
Eval Results (legacy)
text-generation-inference
Instructions to use Jyx0208/C2S-UC-Gemma-2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jyx0208/C2S-UC-Gemma-2B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Jyx0208/C2S-UC-Gemma-2B")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Jyx0208/C2S-UC-Gemma-2B") model = AutoModelForCausalLM.from_pretrained("Jyx0208/C2S-UC-Gemma-2B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Jyx0208/C2S-UC-Gemma-2B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Jyx0208/C2S-UC-Gemma-2B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Jyx0208/C2S-UC-Gemma-2B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Jyx0208/C2S-UC-Gemma-2B
- SGLang
How to use Jyx0208/C2S-UC-Gemma-2B 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 "Jyx0208/C2S-UC-Gemma-2B" \ --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": "Jyx0208/C2S-UC-Gemma-2B", "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 "Jyx0208/C2S-UC-Gemma-2B" \ --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": "Jyx0208/C2S-UC-Gemma-2B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Jyx0208/C2S-UC-Gemma-2B with Docker Model Runner:
docker model run hf.co/Jyx0208/C2S-UC-Gemma-2B
Download training_args.bin from Jyx0208/C2S-UC-Gemma-2B: direct link, hf CLI and curl.
- Browser
- Download file 5.28 kB
-
https://huggingface.co/Jyx0208/C2S-UC-Gemma-2B/resolve/0cd0df58d585abcd4cd94dcf08a0cdbbae21634f/training_args.bin
- Command line
-
hf download hf://Jyx0208/C2S-UC-Gemma-2B@0cd0df58d585abcd4cd94dcf08a0cdbbae21634f/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Jyx0208/C2S-UC-Gemma-2B/resolve/0cd0df58d585abcd4cd94dcf08a0cdbbae21634f/training_args.bin
5.28 kB
- Xet hash:
- af4de9a9acf1f7d8e7c7c83b048c77c207c64964c135a5d44d08cf3bd2b2e813
- Size of remote file:
- 5.28 kB
- SHA256:
- 9f3e2a96819d59e901f3cfb1dd15dd66b50c88c9b54ae6bac01d3fdd27a5d088
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