Firworks/Olmo-3-32B-Think-nvfp4

🤗 Hugging Face 来源apache-2.018.6B 参数20 GBsafetensors✓ 4 个校验和今天更新
一条命令提交

在你的模型文件夹旁边运行它。它会制作种子、将文件与 Hugging Face 比对,然后提交。你只需开始做种,并粘贴你账户中的密钥。它只读取你的文件,绝不修改。如果愿意,可以先阅读脚本。

curl -fsSL https://pirateface.co/package.sh | bash -s -- --repo Firworks/Olmo-3-32B-Think-nvfp4 ./model-folder
需要做种者 →

Olmo-3-32B-Think-nvfp4

Format: NVFP4 — weights & activations quantized to FP4 with dual scaling.
Base model: allenai/Olmo-3-32B-Think
How it was made: One-shot calibration with LLM Compressor (NVFP4 recipe), long-seq calibration with Rombo-Org/Optimized_Reasoning.

Notes: Keep lm_head in high precision; calibrate on long, domain-relevant sequences.

Check the original model card for information about this model.

Running the model with VLLM in Docker

 sudo docker run --runtime nvidia --gpus all    -p  8000:8000   --ipc=host   vllm/vllm-openai:nightly --model Firworks/Olmo-3-32B-Think-nvfp4   --dtype auto   --max-model-len 32768

This was tested on a B200 cloud instance.

If there are other models you're interested in seeing quantized to NVFP4 for use on the DGX Spark, or other modern Blackwell (or newer) cards let me know. I'm trying to make more NVFP4 models available to allow more people to try them out.