Instructions to use EigenLabs/Qwen3.8-27B-MTP-bf16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use EigenLabs/Qwen3.8-27B-MTP-bf16 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Qwen3.8-27B-MTP-bf16 EigenLabs/Qwen3.8-27B-MTP-bf16
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Qwen3.8-27B-MTP-bf16
This is the MTP (multi-token-prediction) head of Qwen/Qwen3.8-27B.
The official model contains this head as 15 mtp.* tensors.
We copied these 15 tensors from revision 1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0.
We removed the mtp. prefix from each tensor name. Example: mtp.fc.weight is now fc.weight.
We did not train the weights. We did not change the weights.
The data type is bfloat16, the same as the official release.
Contents
- One fusion projection (
fc.weight). - One transformer layer with its norms.
config.jsonwithmodel_type: qwen3_5_mtpandblock_size: 3.model.safetensors.index.json. Loaders read the head as its own model tree, so these two files are necessary.
This is not a standalone model
The head predicts draft tokens from the hidden states of its base model. It cannot generate text alone. Use it with the 4-bit reference model: EigenLabs/Qwen3.8-27B-4bit.
Role
The Qwen 3.8 MTP challenge uses this head for speculative decoding.
The track is qwen3.8-27b-mtp-v1.
The challenge repository is Layr-Labs/qwen-3.8-mtp-challenge.
The challenge points to one fixed revision of this repository.
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Model tree for EigenLabs/Qwen3.8-27B-MTP-bf16
Base model
Qwen/Qwen3.8-27B