Instructions to use VGS-AI/DeepSeek-VM-1.5B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VGS-AI/DeepSeek-VM-1.5B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="VGS-AI/DeepSeek-VM-1.5B")# Load model directly from transformers import AutoTokenizer, Qwen2ForClassifier tokenizer = AutoTokenizer.from_pretrained("VGS-AI/DeepSeek-VM-1.5B") model = Qwen2ForClassifier.from_pretrained("VGS-AI/DeepSeek-VM-1.5B") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use VGS-AI/DeepSeek-VM-1.5B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "VGS-AI/DeepSeek-VM-1.5B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "VGS-AI/DeepSeek-VM-1.5B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/VGS-AI/DeepSeek-VM-1.5B
- SGLang
How to use VGS-AI/DeepSeek-VM-1.5B 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 "VGS-AI/DeepSeek-VM-1.5B" \ --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": "VGS-AI/DeepSeek-VM-1.5B", "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 "VGS-AI/DeepSeek-VM-1.5B" \ --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": "VGS-AI/DeepSeek-VM-1.5B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use VGS-AI/DeepSeek-VM-1.5B with Docker Model Runner:
docker model run hf.co/VGS-AI/DeepSeek-VM-1.5B
Improve model card: add pipeline tag, link to paper and code
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by nielsr HF Staff - opened
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library_name: transformers
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# Model Card for Model ID
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1.5B value model for guiding DeepSeek CoT: arxiv.org/abs/2505.17373.
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library_name: transformers
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pipeline_tag: text-classification
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tags: []
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# Model Card for Model ID
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1.5B value model for guiding DeepSeek CoT: arxiv.org/abs/2505.17373.
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[Value-Guided Search for Efficient Chain-of-Thought Reasoning](https://huggingface.co/papers/2505.17373)
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Code: https://github.com/VGS-AI/Value-Guided-Search
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