Text Generation
Transformers
Safetensors
English
pruned_flex_olmo
custom_code
math
pruned
distilled
mixture-of-experts
Instructions to use hbfreed/flex-math-8192 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hbfreed/flex-math-8192 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="hbfreed/flex-math-8192", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("hbfreed/flex-math-8192", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use hbfreed/flex-math-8192 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "hbfreed/flex-math-8192" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "hbfreed/flex-math-8192", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/hbfreed/flex-math-8192
- SGLang
How to use hbfreed/flex-math-8192 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 "hbfreed/flex-math-8192" \ --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": "hbfreed/flex-math-8192", "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 "hbfreed/flex-math-8192" \ --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": "hbfreed/flex-math-8192", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use hbfreed/flex-math-8192 with Docker Model Runner:
docker model run hf.co/hbfreed/flex-math-8192
Upload folder using huggingface_hub
Browse files- model.safetensors +3 -0
- pruning_config.json +5 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:f309b32e672c509af7fb120b74605b4356c8700f0315eac5332cb3263263f068
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size 21040268152
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pruning_config.json
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{
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"base_model": "allenai/Flex-math-2x7B-1T",
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"importance_type": "math",
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"expert_1_width": 8192
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}
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