DeepSeek-V4-Flash-0731-abliterated
from deepseek-ai/DeepSeek-V4-Flash-0731
DeepSeek-V4-Flash-0731-JANG-CRACK is a abliterated and uncensored variant of deepseek-ai/DeepSeek-V4-Flash-0731, published on Hugging Face by dealignai. It is mit licence. It is distributed across 2 repositories in MLX format, totalling 8.2K downloads.
How DeepSeek-V4-Flash-0731-JANG-CRACK was modified, and what that implies.
Abliteration + uncensored fine-tune
Directional ablation combined with additional fine-tuning on unfiltered data, so behaviour diverges from the base model beyond refusal removal alone.
Reported scope: Not stated by the publisher. Publishers frequently omit this, so verify behaviour empirically rather than assuming full coverage.
From the publisher’s model card
“Built for vMLX — the only MLX inferencer with VL support, KV cache quantization, prefix cache reuse, agentic tool calling, and speculative decoding.”
Commands are templates — confirm the exact repository and quant file before use.
from transformers import AutoModelForCausalLM, AutoTokenizer
repo = "dealignai/DeepSeek-V4-Flash-0731-JANG-CRACK"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
repo, torch_dtype="auto", device_map="auto"
)vllm serve dealignai/DeepSeek-V4-Flash-0731-JANG-CRACK --trust-remote-codeThe only published repository of DeepSeek-V4-Flash-0731-JANG-CRACK.
| Repository | Format | Downloads |
|---|---|---|
| dealignai/DeepSeek-V4-Flash-0731-JANG-CRACKsource | MLX | 8.2K |
Derived from this model’s metadata and the publisher’s claims — not from benchmarks run by this site.
Handling: run it isolated, put moderation in front of it if anyone outside your team can reach it, and verify the weights before loading — these are third-party artifacts. Full handling and licence guidance.
Metadata for DeepSeek-V4-Flash-0731-JANG-CRACK is collected from the public Hugging Face API and the publisher’s model card. This site does not host weights, is not affiliated with dealignai, and does not independently verify publisher claims. See responsible use.