Instructions to use unclecode/tinyllama-function-call-lora-adapter-250424 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use unclecode/tinyllama-function-call-lora-adapter-250424 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("unclecode/tinyllama-function-call-lora-adapter-250424", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Unsloth Studio new
How to use unclecode/tinyllama-function-call-lora-adapter-250424 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 unclecode/tinyllama-function-call-lora-adapter-250424 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 unclecode/tinyllama-function-call-lora-adapter-250424 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for unclecode/tinyllama-function-call-lora-adapter-250424 to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="unclecode/tinyllama-function-call-lora-adapter-250424", max_seq_length=2048, )
Function Calling and Tool Use LLaMA Models
This repository contains two main versions of LLaMA models fine-tuned for function calling and tool use capabilities:
- Fine-tuned version of the
LLama3-8b-instructmodel tinyllama- a smaller model version
For each version, the following variants are available:
- 16-bit quantized model
- 4-bit quantized model
- GGFU format for use with llama.cpp
Dataset
The models were fine-tuned using a modified version of the ilacai/glaive-function-calling-v2-sharegpt dataset, which can be found at unclecode/glaive-function-calling-llama3.
Usage
To learn how to use these models, refer to the Colab notebook:
This is the first version of the models, and work is in progress to further train them with multi-tool detection and native tool binding support.
Library and Tools Support
A library is being developed to manage tools and add tool support for major LLMs, regardless of their built-in capabilities. You can find examples and contribute to the library at the following repository:
https://github.com/unclecode/fllm
Please open an issue in the repository for any bugs or collaboration requests.
Other Models
Here are links to other related models:
- unclecode/llama3-function-call-lora-adapter-240424
- unclecode/llama3-function-call-16bit-240424
- unclecode/llama3-function-call-4bit-240424
- unclecode/llama3-function-call-Q4_K_M_GGFU-240424
- unclecode/tinyllama-function-call-lora-adapter-250424
- unclecode/tinyllama-function-call-16bit-250424
- unclecode/tinyllama-function-call-Q4_K_M_GGFU-250424
License
These models are released under the Apache 2.0 license.
Uploaded model
- Developed by: unclecode
- License: apache-2.0
- Finetuned from model : unsloth/llama-3-8b-Instruct-bnb-4bit
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
