Text Generation
Transformers
Safetensors
English
modernbert
fill-mask
phi
nlp
math
code
chat
conversational
Instructions to use sjster/test_v2_medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sjster/test_v2_medium with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="sjster/test_v2_medium")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("sjster/test_v2_medium") model = AutoModelForMaskedLM.from_pretrained("sjster/test_v2_medium", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use sjster/test_v2_medium with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "sjster/test_v2_medium" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "sjster/test_v2_medium", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/sjster/test_v2_medium
- SGLang
How to use sjster/test_v2_medium 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 "sjster/test_v2_medium" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "sjster/test_v2_medium", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "sjster/test_v2_medium" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "sjster/test_v2_medium", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use sjster/test_v2_medium with Docker Model Runner:
docker model run hf.co/sjster/test_v2_medium
Download model.safetensors from sjster/test_v2_medium: direct link, hf CLI and curl.
- Browser
- Download file 599 MB
-
https://huggingface.co/sjster/test_v2_medium/resolve/refs%2Fpr%2F5/model.safetensors
- Command line
-
hf download hf://sjster/test_v2_medium@refs/pr/5/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/sjster/test_v2_medium/resolve/refs%2Fpr%2F5/model.safetensors
599 MB
- Xet hash:
- 52074fe98eef697fbd728eb3628e1bbf5b4d79223a96a23f9179af1e457baeb9
- Size of remote file:
- 599 MB
- SHA256:
- 340ac08b74eef0d7bdec2d7981a6a3d4249bf0e6aab60634b72ad02c2b8023a9
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