Qwen3-4B-2507-abliterated-GGUF

Model overview

> The Huihui-Qwen3-4B-Instruct-2507-abliterated model is an uncensored, proof-of-concept version of the Qwen3-4B-Instruct-2507 large language model, created using a novel abliteration method designed to remove refusal responses without using TransformerLens. This approach offers a faster and more effective way to bypass the model's standard refusal behaviors, resulting in a less filtered and more raw output experience, though it lacks rigorous safety filtering and may generate sensitive or controversial content. The model is quantized (4-bit) for efficient use, can be used directly in Hugging Face’s transformers library, and is intended primarily for research or experimental use rather than production due to the reduced content restrictions and associated risks. Users are advised to carefully monitor outputs and ensure ethical and legal compliance when deploying this model. (sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

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

Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.

Source prices & cost analysis

Prices vary by channel, region and configuration. Channel quotes are listed independently and are not treated as a single official provider price.

Public benchmarks & run configuration

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

Frequently asked questions

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。