Instructions to use lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF", dtype="auto") - llama-cpp-python
How to use lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF", filename="Q2_K-GGUF/Q2_K-GGUF-00001-of-00041.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF:Q2_K # Run inference directly in the terminal: llama-cli -hf lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF:Q2_K
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF:Q2_K # Run inference directly in the terminal: llama-cli -hf lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF:Q2_K
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF:Q2_K # Run inference directly in the terminal: ./llama-cli -hf lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF:Q2_K
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF:Q2_K # Run inference directly in the terminal: ./build/bin/llama-cli -hf lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF:Q2_K
Use Docker
docker model run hf.co/lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF:Q2_K
- LM Studio
- Jan
- vLLM
How to use lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF:Q2_K
- SGLang
How to use lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF 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 "lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'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 "lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }' - Ollama
How to use lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF with Ollama:
ollama run hf.co/lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF:Q2_K
- Unsloth Studio
How to use lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF to start chatting
- Pi
How to use lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF:Q2_K
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF:Q2_K" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF:Q2_K
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF:Q2_K
Run Hermes
hermes
- Atomic Chat new
- Docker Model Runner
How to use lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF with Docker Model Runner:
docker model run hf.co/lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF:Q2_K
- Lemonade
How to use lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull lhca521/Huihui-Kimi-K2.5-BF16-abliterated-GGUF:Q2_K
Run and chat with the model
lemonade run user.Huihui-Kimi-K2.5-BF16-abliterated-GGUF-Q2_K
List all available models
lemonade list
e62d646 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 | ---
license: other
license_name: modified-mit
library_name: transformers
pipeline_tag: image-text-to-text
base_model:
- moonshotai/Kimi-K2.5
tags:
- abliterated
- uncensored
- GGUF
---
# huihui-ai/Huihui-Kimi-K2.5-BF16-abliterated-GGUF
This is an uncensored version of [moonshotai/Kimi-K2.5](https://huggingface.co/moonshotai/Kimi-K2.5) created with abliteration (see [remove-refusals-with-transformers](https://github.com/Sumandora/remove-refusals-with-transformers) to know more about it).
## Download and merge
[Q2_K](https://huggingface.co/huihui-ai/Huihui-Kimi-K2.5-BF16-abliterated-GGUF/tree/main/Q2_K-GGUF)
[Q3_K](https://huggingface.co/huihui-ai/Huihui-Kimi-K2.5-BF16-abliterated-GGUF/tree/main/Q3_K-GGUF)
Use the [llama.cpp](https://github.com/ggml-org/llama.cpp) split program to merge model (llama-gguf-split needs to be compiled.),
```
huggingface-cli download huihui-ai/Huihui-Kimi-K2.5-BF16-abliterated-GGUF --local-dir ./huihui-ai/Huihui-Kimi-K2.5-BF16-abliterated-GGUF --token xxx
llama-gguf-split --merge huihui-ai/Huihui-Kimi-K2.5-BF16-abliterated-GGUF/Q2_K-GGUF/Q2_K-GGUF-00001-of-00041.gguf huihui-ai/Huihui-Kimi-K2.5-BF16-abliterated-GGUF/Q2_K.gguf
```
## Process image
```
llama-mtmd-cli -m huihui-ai/Huihui-Kimi-K2.5-BF16-abliterated-GGUF/Q2_K.gguf --mmproj huihui-ai/Huihui-Kimi-K2.5-BF16-abliterated-GGUF/mmproj-model-f16.gguf -c 40960 --image cars.jpg -p "Describe this image"
```
# Tool Calling
By using llama-serve and the opencode test Tool Calling, it is evident that the performance is excellent.
```
llama-server -m huihui-ai/Huihui-Kimi-K2.5-BF16-abliterated-GGUF/Q3_K.gguf --port 8080 --host 0.0.0.0 -c 262144
```
The following are the relevant configurations for openconde.json used in a Docker environment.
```
{
"$schema": "https://opencode.ai/config.json",
"provider": {
"llama-server": {
"npm": "@ai-sdk/openai-compatible",
"name": "llama-server",
"options": {
"baseURL": "http://host.docker.internal:8080/v1"
},
"models": {
"Huihui-Kimi-K2.5-BF16-abliterated-Q3_K": {
"name": "Huihui-Kimi-K2.5-BF16-abliterated-Q3_K",
"tools": true,
"reasoning": false,
"options": {
"num_ctx": 262144
}
}
}
}
}
}
```
### 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
```
- Support our work on Ko-fi (https://ko-fi.com/huihuiai)!
|