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bloopez/Huihui-GLM-4.7-Flash-abliterated-BF16-GGUF
Huihui-GLM-4.7-Flash-abliterated-BF16-GGUF is a text generation model from bloopez. Use it when you need the model to write or continue text. The card lists the license as mit.
GGUF conversion of huihui-ai/Huihui-GLM-4.7-Flash-abliterated at full BF16 precision.
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.gguf59.9 GB · 100%
From the Hugging Face model README
GGUF conversion of huihui-ai/Huihui-GLM-4.7-Flash-abliterated at full BF16 precision.
The standard convert_hf_to_gguf.py produced broken output for glm4_moe_lite at the time of creation (January 2026), so this was produced via binary patching of verified working GGUF files.
| Property | Value |
|---|---|
| Architecture | GLM-4.7-Flash (30B-A3B MoE, DeepSeek2-like) |
| Active Parameters | ~3B per token |
| Total Parameters | ~30B |
| Experts | 64 routed + 1 shared (4 active per token) |
| Precision | BF16 (full precision, no quantization) |
| Context Length | Up to 202K tokens (tested at 128K) |
| Files | 2 split GGUF files (~56GB total) |
| Tensors | 844 patched, 0 errors |
Instead of using the broken converter, this model was created by:
kv_b_proj (8960x512) reshaped and split into separate k_b (20x512x192, transposed) and v_b (20x256x512) tensorsThis approach inherits all gating function fixes and correct GGUF structure from unsloth's conversion.
Note: Internal GGUF metadata (e.g., general.name, general.quantized_by) reflects the original unsloth source files. Only tensor data was replaced.
This is an abliterated (uncensored) model. Safety filtering has been significantly reduced. This model:
The creator bears no responsibility for any consequences arising from the use of this model. Users must ensure compliance with local laws and ethical standards.
MIT (inherited from base models)
Huihui-GLM-4.7-Flash-abliterated-BF16-00001-of-00002.gguf (49.9 GB)
Huihui-GLM-4.7-Flash-abliterated-BF16-00002-of-00002.gguf (10.0 GB)