Trellis
exllamav3
deepseek_v4
exl3
Mixture of Experts
mixed-precision
uncensored
abliterated
dgx-spark
2-bit
Instructions to use vcruz305/DSV4-Flash-Vision-ablit-EXL3-MixedK with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Trellis
How to use vcruz305/DSV4-Flash-Vision-ablit-EXL3-MixedK with Trellis:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
DeepSeek-V4-Flash-Vision-Exp (abliterated) — EXL3 MixedK
Uncensored variant of the DSV4-Flash-Vision MixedK pack, derived by anchored splice from drowzeys/keys-DeepSeekV4Flash-Vision-EXP-ablit.
How it was made
The upstream abliteration is an anchored-tensor edit: it modifies only
26 attention output projections (layers.10-35.attn.wo_b.weight, lambda 3.5),
leaving all experts, the MTP/DSpark drafter, and vision untouched. Those 26
tensors are BF16 natives in our pack, so this variant is the MixedK pack with
exactly those 26 tensors swapped for their abliterated versions — no
re-encoding. Every expert is byte-identical to the non-abliterated MixedK.
Notes
- ~95 GiB, fits one DGX Spark. Format, serving, and limitations are identical to the non-ablit MixedK (mixed-format, not boot-tested, K2 double-quant).
- Uncensored: safety refusals removed upstream. For red-teaming / security research / evaluation. You bear deployment responsibility.
- DeepSeek license (
other) + the upstream Responsible Use terms.
- Downloads last month
- 156
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support
Model tree for vcruz305/DSV4-Flash-Vision-ablit-EXL3-MixedK
Base model
deepseek-ai/DeepSeek-V4-Flash-Vision-Exp