Instructions to use Youssofal/Kimi-K2.6-Abliterated-Heretic-BF16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Youssofal/Kimi-K2.6-Abliterated-Heretic-BF16 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("image-text-to-text", model="Youssofal/Kimi-K2.6-Abliterated-Heretic-BF16", trust_remote_code=True)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Youssofal/Kimi-K2.6-Abliterated-Heretic-BF16", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Youssofal/Kimi-K2.6-Abliterated-Heretic-BF16 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Youssofal/Kimi-K2.6-Abliterated-Heretic-BF16"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Youssofal/Kimi-K2.6-Abliterated-Heretic-BF16",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Youssofal/Kimi-K2.6-Abliterated-Heretic-BF16

SGLang

How to use Youssofal/Kimi-K2.6-Abliterated-Heretic-BF16 with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "Youssofal/Kimi-K2.6-Abliterated-Heretic-BF16" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Youssofal/Kimi-K2.6-Abliterated-Heretic-BF16",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "Youssofal/Kimi-K2.6-Abliterated-Heretic-BF16" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Youssofal/Kimi-K2.6-Abliterated-Heretic-BF16",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Youssofal/Kimi-K2.6-Abliterated-Heretic-BF16 with Docker Model Runner:
```
docker model run hf.co/Youssofal/Kimi-K2.6-Abliterated-Heretic-BF16
```

🚨 UPLOADS IN PROGRESS 🚨

Some files and metadata in this repository are still being uploaded and verified.

Kimi-K2.6-Abliterated-Heretic-BF16

A BF16 abliterated Kimi-K2.6 checkpoint produced with Heretic.

Quick Benchmarks

Check	Original Kimi-K2.6	Abliterated Heretic BF16
Official 25-prompt refusal check	Pending	Pending
Archived Heretic KL divergence	Pending	Pending

Abliteration notes:

base model: moonshotai/Kimi-K2.6
method family: text-side Heretic intervention with multimodal wrapper preserved
official refusal check: pending
multimodal path preserved; intervention is limited to the language-model stack

Notes:

GGUF quants are published separately in Youssofal/Kimi-K2.6-Abliterated-Heretic-GGUF
Export metadata for the accepted candidate will be included after the final checkpoint is validated

Downloads last month: -; Downloads are not tracked for this model. How to track

Inference Providers NEW

Image-Text-to-Text

This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for Youssofal/Kimi-K2.6-Abliterated-Heretic-BF16

Base model

moonshotai/Kimi-K2.6

Finetuned

(18)

this model