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spinochenza/Huihui-Kimi-Linear-REAP-35B-A3B-Instruct-abliterated

spinochenza Kimi 35B MoE
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Response includes
  • classification m1
  • files 27
  • hub_downloads_all_time 102
  • author_summary 17 models
  • readme_text full
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Abliteration classifier · v1.0.0
M1
Primary method

Direct removal

No other method signals detected in this model.
Confidence
MEDIUM
Why this label 3 signals
Method inferred from partial signals - repository name, related files, or tag patterns. Producer identity not confirmed; label may sharpen or shift as we gather more evidence.
  • 'abliterated' in name/tags
  • is_gguf=0 (base model)
  • no specific method indicators - defaulting to M1 (most common)
Refusal direction extracted via
Extraction technique

Difference-of-means

Confidence
MEDIUM
Why we say so
primary_method=M1; difference-of-means is the reference extraction for M1/M3 (Arditi 2024)
Downloads · lifetime
102
20 last 30d - stable
Likes
1
Model age
4mo ago
created 2026-06-04
Downloads over time
Now113→from16↑606%
11488612316 on Jun 10113 on Oct 11113 on Oct 9JunJulAugSepOct
Jun 10 → Oct 11 · 57 snapshots · spans 123 days

Genealogy 0 direct forks

Full fork graph →

This model's place in the market. Above: what it was derived from. Below: the tree of everything derived from it.

Metadata

License
mit
Tags
transformers safetensors kimi_linear text-generation abliterated uncensored conversational custom_code base_model:cerebras/Kimi-Linear-REAP-35B-A3B-Instruct base_model:finetune:cerebras/Kimi-Linear-REAP-35B-A3B-Instruct license:mit endpoints_compatible

Related

Total size
65.4 GB
Files
27
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2026-06-04 16:43

Files by quantization

Auxiliary files 27 files 65.4 GB
model-00012-of-00015.safetensors 4.66 GB b3da3e9b download
model-00008-of-00015.safetensors 4.66 GB 37a273ba download
model-00010-of-00015.safetensors 4.66 GB e2499192 download
model-00002-of-00015.safetensors 4.66 GB abf272bb download
model-00004-of-00015.safetensors 4.66 GB ab94508d download
model-00001-of-00015.safetensors 4.66 GB b977280c download
model-00013-of-00015.safetensors 4.65 GB 63eb4bc9 download
model-00011-of-00015.safetensors 4.65 GB a1646f9c download
model-00009-of-00015.safetensors 4.65 GB a82f1c6d download
model-00005-of-00015.safetensors 4.65 GB 4081838b download
model-00003-of-00015.safetensors 4.65 GB 3a6d451a download
model-00007-of-00015.safetensors 4.65 GB 9071dd51 download
model-00006-of-00015.safetensors 4.65 GB b45769ea download
model-00014-of-00015.safetensors 4.24 GB 6894b5fb download
model-00015-of-00015.safetensors 720 MB f48b38d4 download
tiktoken.model 2.67 MB b6c497a7 download
model.safetensors.index.json 1.34 MB aae6c208 download
modeling_kimi.py 39.8 KB 4f296a21 download
tokenization_kimi.py 12.2 KB 37f3c23d download
configuration_kimi.py 4.83 KB 2d66544a download
README.md 2.87 KB 1747871f download
tokenizer_config.json 2.67 KB d95af523 download
chat_template.jinja 1.81 KB 2ed21577 download
config.json 1.71 KB a8fa27ba download
.gitattributes 1.48 KB a6344aac download
special_tokens_map.json 760 B 08abeea2 download
generation_config.json 147 B 65082b17 download

README current version from Hugging Face


license: mit
pipeline_tag: text-generation
library_name: transformers
base_model:

  • cerebras/Kimi-Linear-REAP-35B-A3B-Instruct
    tags:
  • abliterated
  • uncensored

huihui-ai/Huihui-Kimi-Linear-REAP-35B-A3B-Instruct-abliterated

This is an uncensored version of cerebras/Kimi-Linear-REAP-35B-A3B-Instruct created with abliteration (see remove-refusals-with-transformers to know more about it).

Inference with Hugging Face Transformers

from transformers import AutoModelForCausalLM, AutoTokenizer

model_name = "huihui-ai/Huihui-Kimi-Linear-REAP-35B-A3B-Instruct-abliterated"
model = AutoModelForCausalLM.from_pretrained(
    model_name,
    torch_dtype="auto",
    device_map="auto",
    trust_remote_code=True
)
tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)

messages = [
    {"role": "system", "content": "You are a helpful assistant provided by Moonshot-AI."},
    {"role": "user", "content": "Is 123 a prime?"}
]
input_ids = tokenizer.apply_chat_template(
    messages, 
    add_generation_prompt=True, 
    return_tensors="pt"
).to(model.device)
generated_ids = model.generate(inputs=input_ids, max_new_tokens=500)
response = tokenizer.batch_decode(generated_ids)[0]
print(response)

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

Your donation helps us continue our further development and improvement, a cup of coffee can do it.
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README history 1 version

The author's README evolved over time. Click a version to see its content at that point.

  1. 2026-06-04Duplicate from KimiRio/Huihui-Kimi-Linear-REAP-35B-A3B-Instruct-abliterated3fccd772.9 KB
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