Instructions to use a36tran/Hearo-3B-v1-adapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Local Apps Settings
- Unsloth Studio
How to use a36tran/Hearo-3B-v1-adapter 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 a36tran/Hearo-3B-v1-adapter 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 a36tran/Hearo-3B-v1-adapter to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for a36tran/Hearo-3B-v1-adapter to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="a36tran/Hearo-3B-v1-adapter", max_seq_length=2048, )
Hearo-3B-v1-adapter : GGUF
This model was finetuned and converted to GGUF format using Unsloth.
Example usage:
- For text only LLMs:
./llama.cpp/llama-cli -hf Hearo-3B-v1-adapter --jinja - For multimodal models:
./llama.cpp/llama-mtmd-cli -hf Hearo-3B-v1-adapter --jinja
Available Model files:
qwen2.5-3b-instruct.F16.gguf
Ollama
An Ollama Modelfile is included for easy deployment.
This was trained 2x faster with Unsloth

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