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ussoewwin/qwen3_4b_8b_abliterated_fp16_convrot_int8

sourceHugging Faceapache-2.0updated 1mo agoView on Hugging Face
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Model Card

Qwen3 Abliterated FP16 Collection

This repository is a unified model card for FP16 single-file safetensors conversions of Qwen3 abliterated variants. It is maintained as a combined release line for 4B, 8B, and VL-4B-Thinking models.

Model Scope

VariantUpstream BaseFormatStatus
4Bhuihui-ai/Qwen3-4B-abliteratedSingle .safetensors in FP16Available
8Bhuihui-ai/Qwen3-8B-abliteratedSingle .safetensors in FP16Available
VL 4B Thinkinghuihui-ai/Huihui-Qwen3-VL-4B-Thinking-abliteratedSingle .safetensors in FP16Available

Repository Files

  • —qwen3_4b_abliterated_fp16_converted.safetensors
  • —Qwen3-8B-abliterated-fp16.safetensors
  • —Qwen3_VL_4B_Thinking_abliterated.safetensors

Conversion Workflow

  1. 1.Download sharded safetensors from the respective upstream repositories.
  2. 2.Merge all shard files into one tensor file.
  3. 3.Convert all weights to FP16.
  4. 4.Save as a single safetensors artifact.

Usage (Transformers)

python
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

model_id = "ussoewwin/qwen3_4b_8b_abliterated_fp16"

# Load the specific text-generation safetensors file you need
model = AutoModelForCausalLM.from_pretrained(
    model_id,
    torch_dtype=torch.float16,
    device_map="auto",
    trust_remote_code=True,
)
tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)

messages = [{"role": "user", "content": "Hello, how are you?"}]
input_ids = tokenizer.apply_chat_template(
    messages,
    tokenize=True,
    add_generation_prompt=True,
    return_tensors="pt",
).to(model.device)

outputs = model.generate(input_ids, max_new_tokens=512)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(response)

(For the VL model, refer to standard Qwen-VL-Chat loading procedures utilizing `qwen_vl_utils`)

Important Usage Notes

  • —This model family has reduced safety filtering compared to standard aligned chat checkpoints.
  • —Validate generated text before production or public deployment.
  • —Use in compliance with local laws, platform policies, and your own risk controls.

License

This repository follows Apache 2.0. Please also follow the upstream licenses and terms for each source model.

Acknowledgments

  • —4B source: huihui-ai/Qwen3-4B-abliterated
  • —8B source: huihui-ai/Qwen3-8B-abliterated
  • —VL 4B source: huihui-ai/Huihui-Qwen3-VL-4B-Thinking-abliterated
  • —Original base family: Qwen/Qwen3

Citation

If you use these models, please cite the original Qwen3 work:

bibtex
@misc{qwen3,
  title={Qwen3: A Large-Scale Multilingual Language Model},
  author={Qwen Team},
  year={2024},
  howpublished={\url{https://github.com/QwenLM/Qwen3}}
}