dima6312/Flint-40B-A2.5B-abliterated-NVFP4-GGUF
text-generation model by dima6312
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Model card & documentation
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An abliterated (uncensored) Flint: RecursiveSI's Flint 40B-A2.5B with its refusal direction removed, for security research and coding work, as an NVFP4 GGUF for NVIDIA Blackwell GPUs with llama.cpp CUDA. Summary: held-out MITRE ATT&CK refusals 15% → 0% (n=100, Q80). No significant drop on HumanEval+, MBPP+, GSM8K, MMLU-Pro, CyberMetric or WMDP-cyber (paired, same items). KL divergence from the original on harmless prompts: 0.0146. Builds: BF16, GGUF (Q80 to Q3KM), NVFP4 for NVIDIA Blackwell, MLX 4-bit for Apple silicon. Not sure? Take the GGUF Q4KM (24 GB). It runs in llama.cpp and in apps built on it, including LM Studio (its llama.cpp runtime 2.63.0 includes Flint). The MLX builds are for Mac users who already run mlx-lm. Plan for the file size plus memory for context: about 26 KB per token, so roughly 7 GB at the full 262,144 tokens. The file Flint-40B-A2.5B-abliterated-NVFP4.gguf (22.9 GB) uses the same tensor layout, types and…
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Model overview
dima6312/Flint-40B-A2.5B-abliterated-NVFP4-GGUF is a text-generation model repository published by dima6312 on Hugging Face. The source reports the gguf library.
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Model facts
- Task
- text-generation
- Library
- gguf
- Recent downloads (30 days)
- 0
- Cumulative likes
- 0
- Hugging Face trending score
- 0
- Reported safetensors parameters
- Not reported
- Architecture
- Not reported
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2026-10-23T06:36:03.000Z
- Last modified
- 2026-10-23T06:41:24.000Z
Compatibility and lineage
Reported languages: en
Reported base models: dima6312/Flint-40B-A2.5B-abliterated
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-10-23T06:46:00.441Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.