This repository provides an NVFP4-format derivative based on
huihui-ai/Huihui-Qwen3.5-4B-abliterated, which itself is derived from
Qwen/Qwen3.5-4B.
The main purpose of this release is research on inference depth, runtime behavior, and deployment characteristics of NVFP4 models. It is intended for study, benchmarking, and controlled experimentation rather than general-purpose safe deployment.
This model card intentionally preserves the provenance of the original Huihui release. The original fine-tuning characteristics, output tendencies, and risk profile should be assumed to carry over unless you independently verify otherwise in your own environment.
Use of this model is entirely at your own risk.
The fine-tuned dataset is a type of dataset that operates in a non-think mode, and it may actually make thinking simpler.
It was only the text part that was processed, not the image part.
After saving the model, the names of some weights have changed, and it no longer contains MTP weights. However, both ollama and llama.cpp can still be used for conversion.
Please use the latest version of
ollama v0.17.7
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Risk of Sensitive or Controversial Outputs: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs.
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Not Suitable for All Audiences: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security.
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Legal and Ethical Responsibilities: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences.
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Research and Experimental Use: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications.
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Monitoring and Review Recommendations: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content.
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No Default Safety Guarantees: Unlike standard models, this model has not undergone rigorous safety optimization. The original fine-tuned source and this NVFP4 derivative should both be treated as research artifacts, and the publisher bears no responsibility for any consequences arising from their use.
