Instructions to use Trilogix1/Anthropics-Fable-finetuned-in-Qwen3.6-35B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use Trilogix1/Anthropics-Fable-finetuned-in-Qwen3.6-35B with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Trilogix1/Anthropics-Fable-finetuned-in-Qwen3.6-35B", filename="Anthropics-Fable-Qwen3.6-35b.IQ4_NL.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Trilogix1/Anthropics-Fable-finetuned-in-Qwen3.6-35B with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf Trilogix1/Anthropics-Fable-finetuned-in-Qwen3.6-35B:IQ4_NL # Run inference directly in the terminal: llama cli -hf Trilogix1/Anthropics-Fable-finetuned-in-Qwen3.6-35B:IQ4_NL
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Trilogix1/Anthropics-Fable-finetuned-in-Qwen3.6-35B:IQ4_NL # Run inference directly in the terminal: llama cli -hf Trilogix1/Anthropics-Fable-finetuned-in-Qwen3.6-35B:IQ4_NL
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 Trilogix1/Anthropics-Fable-finetuned-in-Qwen3.6-35B:IQ4_NL # Run inference directly in the terminal: ./llama-cli -hf Trilogix1/Anthropics-Fable-finetuned-in-Qwen3.6-35B:IQ4_NL
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 Trilogix1/Anthropics-Fable-finetuned-in-Qwen3.6-35B:IQ4_NL # Run inference directly in the terminal: ./build/bin/llama-cli -hf Trilogix1/Anthropics-Fable-finetuned-in-Qwen3.6-35B:IQ4_NL
Use Docker
docker model run hf.co/Trilogix1/Anthropics-Fable-finetuned-in-Qwen3.6-35B:IQ4_NL
- LM Studio
- Jan
- Ollama
How to use Trilogix1/Anthropics-Fable-finetuned-in-Qwen3.6-35B with Ollama:
ollama run hf.co/Trilogix1/Anthropics-Fable-finetuned-in-Qwen3.6-35B:IQ4_NL
- Unsloth Studio
How to use Trilogix1/Anthropics-Fable-finetuned-in-Qwen3.6-35B 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 Trilogix1/Anthropics-Fable-finetuned-in-Qwen3.6-35B 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 Trilogix1/Anthropics-Fable-finetuned-in-Qwen3.6-35B to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Trilogix1/Anthropics-Fable-finetuned-in-Qwen3.6-35B to start chatting
- Pi
How to use Trilogix1/Anthropics-Fable-finetuned-in-Qwen3.6-35B with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Trilogix1/Anthropics-Fable-finetuned-in-Qwen3.6-35B:IQ4_NL
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": "Trilogix1/Anthropics-Fable-finetuned-in-Qwen3.6-35B:IQ4_NL" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use Trilogix1/Anthropics-Fable-finetuned-in-Qwen3.6-35B with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Trilogix1/Anthropics-Fable-finetuned-in-Qwen3.6-35B:IQ4_NL
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 Trilogix1/Anthropics-Fable-finetuned-in-Qwen3.6-35B:IQ4_NL
Run Hermes
hermes
- Atomic Chat new
- Docker Model Runner
How to use Trilogix1/Anthropics-Fable-finetuned-in-Qwen3.6-35B with Docker Model Runner:
docker model run hf.co/Trilogix1/Anthropics-Fable-finetuned-in-Qwen3.6-35B:IQ4_NL
- Lemonade
How to use Trilogix1/Anthropics-Fable-finetuned-in-Qwen3.6-35B with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Trilogix1/Anthropics-Fable-finetuned-in-Qwen3.6-35B:IQ4_NL
Run and chat with the model
lemonade run user.Anthropics-Fable-finetuned-in-Qwen3.6-35B-IQ4_NL
List all available models
lemonade list
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 Trilogix1/Anthropics-Fable-finetuned-in-Qwen3.6-35B:IQ4_NLRun Hermes
hermes- Credit to Qwen team for the model creation
- Credit to https://huggingface.co/lordx64/Qwable-v1 for the finetuning work
- Credit to LLama.cpp team for the great contribution
- Credit to Hugston Team for Converting, Quantizing, Testing, Benching and other...
- Credit to Huggingface for the amazing hosting platform
This is a converted and quantized version of Qwen 3.6 35B using Quanta and HugstonOne.
model size = 132219.74 MiB (32.00 BPW)
quant size = 21192.47 MiB (5.13 BPW)
Original weights here: https://huggingface.co/lordx64/Qwable-v1
Credit to Qwen team for the model creation
Credit to https://huggingface.co/lordx64/Qwable-v1 for the finetuning work
Credit to LLama.cpp team for the great contribution
Credit to Hugston Team for Converting, Quantizing, Testing, Benching and other...
Credit to Huggingface for the amazing hosting platform
The quantization in GGUF was made in f32 for better quality quants.
Here we show Quanta our convertor and Quantizer tool.
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Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp# Start a local OpenAI-compatible server: llama serve -hf Trilogix1/Anthropics-Fable-finetuned-in-Qwen3.6-35B:IQ4_NL