MODEL PROFILE

Qwen3.8-27B-Uncensored

JonathanColetti · Qwen3.8-27B-Uncensored

These are the bf16 safetensors. For local inference under llama.cpp, see JonathanColetti/Qwen3.8-27B-Uncensored-GGUF, which ships imatrix quantizations with the multi-token prediction head retained. Try it first in the demo Space. > **The MTP head is present and verified.** Abliteration drops the `mtp.*` tensors: the > model is re-saved through transformers, which does not carry the MTP module, while > `config.json` still advertises `mtp_num_hidden_layers`. All 15 `mtp.*` tensors were > grafted back from the base checkpoint and the inventory was asserted against the source > before upload. - Refusal directions removed with Heretic, which co-minimizes refusal count against KL divergence from the base model. No hand-written refusal-removal code, no fine-tuning, no additional training data. - Abliteration runs at bf16 (no 4-bit quantization); the resulting LoRA is merged into the bf16 base, so these weights are not a quantized round trip. - Only `attn.o_proj` and `mlp.down_proj` are modified, 64 modules each. The `mtp.*` tensors are copied verbatim from the base checkpoint after merging. - 200 optimization trials. The published checkpoint is one point on the resulting Pareto front, selected for the lowest refusal count; the full front is below.

Visual QAlicense:apache-2.0
Context windowNot disclosed
Input → OutputText、Image → Text
Model weightsNot verified
Profile updated2026/11/2 19:15:53
OVERVIEW

Model overview

These are the bf16 safetensors. For local inference under llama.cpp, see JonathanColetti/Qwen3.8-27B-Uncensored-GGUF, which ships imatrix quantizations with the multi-token prediction head retained. Try it first in the demo Space. > **The MTP head is present and verified.** Abliteration drops the `mtp.*` tensors: the > model is re-saved through transformers, which does not carry the MTP module, while > `config.json` still advertises `mtp_num_hidden_layers`. All 15 `mtp.*` tensors were > grafted back from the base checkpoint and the inventory was asserted against the source > before upload. - Refusal directions removed with Heretic, which co-minimizes refusal count against KL divergence from the base model. No hand-written refusal-removal code, no fine-tuning, no additional training data. - Abliteration runs at bf16 (no 4-bit quantization); the resulting LoRA is merged into the bf16 base, so these weights are not a quantized round trip. - Only `attn.o_proj` and `mlp.down_proj` are modified, 64 modules each. The `mtp.*` tensors are copied verbatim from the base checkpoint after merging. - 200 optimization trials. The published checkpoint is one point on the resulting Pareto front, selected for the lowest refusal count; the full front is below.

Key features

特点摘要待依据来源补齐,不凭模型名称推断能力。

Limitations & considerations

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PRICING & COST

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INDEPENDENT BENCHMARKS

Public benchmarks & run configuration

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Sources & traceability

许可证:apache-2.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。