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Model: huihui-ai/Huihui-Qwen3-4B-Thinking-2507-abliterated-w4g128
Source: Original Platform

README.md

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+---
+library_name: transformers
+license: apache-2.0
+license_link: https://huggingface.co/Qwen/Qwen3-4B-Thinking-2507/blob/main/LICENSE
+base_model:
+- huihui-ai/Huihui-Qwen3-4B-Thinking-2507-abliterated
+pipeline_tag: text-generation
+tags:
+- abliterated
+- uncensored
+- auto-round
+---
+# huihui-ai/Huihui-Qwen3-4B-Thinking-2507-abliterated-w4g128
+
+This is an uncensored **Quantized** version of [Qwen/Qwen3-4B-Thinking-2507](https://huggingface.co/Qwen/Qwen3-4B-Thinking-2507) created with abliteration (see [remove-refusals-with-transformers](https://github.com/Sumandora/remove-refusals-with-transformers) to know more about it).
+This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. 
+
+## Quantized
+
+Quantized using the Intel [auto-round](https://github.com/intel/auto-round) tool with weight-only quantization (Weight-Only INT4, group_size=128), achieving excellent precision retention at low bits with almost no noticeable quality degradation.
+
+```
+auto-round-best --model huihui-ai/Qwen3-4B-Thinking-2507-abliterated \
+  --scheme "W4A16" \
+  --format auto_round \
+  --output_dir huihui-ai/Qwen3-4B-Thinking-2507-abliterated-w4g128 \
+  --enable_torch_compile
+```
+
+# Transformers
+
+```
+pip install "auto-round>=0.5"
+```
+
+```
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+NEW_MODEL_ID = "huihui-ai/Huihui-Qwen3-4B-Thinking-2507-abliterated-w4g128"
+model = AutoModelForCausalLM.from_pretrained(
+    NEW_MODEL_ID, 
+    device_map="auto", 
+    trust_remote_code=True,
+)
+tokenizer = AutoTokenizer.from_pretrained(NEW_MODEL_ID, trust_remote_code=True)
+```
+
+
+## vllm
+
+```
+python -m vllm.entrypoints.openai.api_server \
+    --model huihui-ai/Qwen3-4B-Thinking-2507-abliterated-w4g128 \
+    --max-model-len 8192
+```
+
+
+
+### Usage Warnings
+
+
+ - **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.
+
+ - **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.
+
+ - **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.
+
+ - **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.
+
+ - **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.
+
+ - **No Default Safety Guarantees**: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use.
+
+
+### Donation
+
+If you like it, please click 'like' and follow us for more updates.  
+You can follow [x.com/support_huihui](https://x.com/support_huihui) to get the latest model information from huihui.ai.
+
+##### Your donation helps us continue our further development and improvement, a cup of coffee can do it.
+- bitcoin（BTC):
+```
+  bc1qqnkhuchxw0zqjh2ku3lu4hq45hc6gy84uk70ge
+```
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