Instructions to use jan-hq/stealth-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jan-hq/stealth-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="jan-hq/stealth-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("jan-hq/stealth-v2") model = AutoModelForCausalLM.from_pretrained("jan-hq/stealth-v2") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use jan-hq/stealth-v2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "jan-hq/stealth-v2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "jan-hq/stealth-v2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/jan-hq/stealth-v2
- SGLang
How to use jan-hq/stealth-v2 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 "jan-hq/stealth-v2" \ --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": "jan-hq/stealth-v2", "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 "jan-hq/stealth-v2" \ --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": "jan-hq/stealth-v2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use jan-hq/stealth-v2 with Docker Model Runner:
docker model run hf.co/jan-hq/stealth-v2
Prompt template
ChatML
<|im_start|>system
{system_message}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
Training detail
You can read here.
Run this model
You can run this model using Jan Desktop on Mac, Windows, or Linux.
Jan is an open source, ChatGPT alternative that is:
💻 100% offline on your machine: Your conversations remain confidential, and visible only to you.
🗂️ ** An Open File Format**: Conversations and model settings stay on your computer and can be exported or deleted at any time.
🌐 OpenAI Compatible: Local server on port
1337with OpenAI compatible endpoints🌍 Open Source & Free: We build in public; check out our Github
About Jan
Jan believes in the need for an open-source AI ecosystem and is building the infra and tooling to allow open-source AIs to compete on a level playing field with proprietary ones.
Jan's long-term vision is to build a cognitive framework for future robots, who are practical, useful assistants for humans and businesses in everyday life.
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 76.37 |
| AI2 Reasoning Challenge (25-Shot) | 73.89 |
| HellaSwag (10-Shot) | 89.26 |
| MMLU (5-Shot) | 64.94 |
| TruthfulQA (0-shot) | 72.47 |
| Winogrande (5-shot) | 88.00 |
| GSM8k (5-shot) | 69.67 |
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Model tree for jan-hq/stealth-v2
Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard73.890
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard89.260
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard64.940
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard72.470
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard88.000
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard69.670
