Instructions to use dgrauet/void-model-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use dgrauet/void-model-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download dgrauet/void-model-mlx --local-dir void-model-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Commit History
-
Refresh the card so its own manifest size line is current
Verified signature0502025 -
Add the usage snippet, taken from the inference project's own README
Verified signature32176b6 -
Add the usage snippet, taken from the inference project's own README
Verified signature0c18b47
-
Record the base-model link per build, as it differs between bf16 and quantized
Verified signature7464db4 -
Record the base-model link per build, as it differs between bf16 and quantized
Verified signature4f0e82a -
Record the repo's sibling links in the manifest
Verified signature57bbd68 -
Record the repo's sibling links in the manifest
Verified signature7bc8dd3 -
Add split_model.json so the repo identifies its recipe
Verified signature9610fc9
-
Restore bf16 weights (revert accidental test upload)
Verified signatureCommit 4ab52707 replaced void_pass1/2.safetensors with 65 KB synthetic tensors from a local test run. This restores the 11.1 GB weights and the README from 1bfe381b by server-side copy, and removes the split_model.json that commit introduced.363c888 -
Upload MLX model via mlx-forge
Verified signature4ab5270
-
Upload VOID model MLX (bf16)
Verified signature1bfe381 -
initial commit
Verified signature85249e3