Instructions to use Jinx-org/Jinx-gpt-oss-20b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jinx-org/Jinx-gpt-oss-20b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Jinx-org/Jinx-gpt-oss-20b") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Jinx-org/Jinx-gpt-oss-20b") model = AutoModelForCausalLM.from_pretrained("Jinx-org/Jinx-gpt-oss-20b") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use Jinx-org/Jinx-gpt-oss-20b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Jinx-org/Jinx-gpt-oss-20b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Jinx-org/Jinx-gpt-oss-20b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Jinx-org/Jinx-gpt-oss-20b
- SGLang
How to use Jinx-org/Jinx-gpt-oss-20b 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 "Jinx-org/Jinx-gpt-oss-20b" \ --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": "Jinx-org/Jinx-gpt-oss-20b", "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 "Jinx-org/Jinx-gpt-oss-20b" \ --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": "Jinx-org/Jinx-gpt-oss-20b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Jinx-org/Jinx-gpt-oss-20b with Docker Model Runner:
docker model run hf.co/Jinx-org/Jinx-gpt-oss-20b
Will you consider doing one for GLM Air?
I'd love to see how a Jinx version of GLM-Air behaves. Would you consider doing one?
Thanks for you interest. But building more Jinx version of LLMs are NOT prioritized. We are building VLM currently.
Best,
Jinx Team
Yep I would also be interested, GLM (and Air) is currently the only open source model I've found that rivals Opus 4 (based on actual usage, & custom evals metrics). Unfortunately, it's heavily biased/censored with lots of refusals though. I understand if it's not your priority and that's fine, thanks for all your work, but I would be interested to see a more unbiased/uncensored version it it became interesting for you at some point. I'd even be interested in making a donation toward training costs if you're interested - feel free reach out.