Safetensors
GGUF
Turkish
llama
Llama-3
instruct
finetune
chatml
gpt4
synthetic data
distillation
function calling
json mode
axolotl
roleplaying
chat
Instructions to use tda45/TdAI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use tda45/TdAI with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="tda45/TdAI", filename="llama.cpp/models/ggml-vocab-aquila.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use tda45/TdAI 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 tda45/TdAI # Run inference directly in the terminal: llama cli -hf tda45/TdAI
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf tda45/TdAI # Run inference directly in the terminal: llama cli -hf tda45/TdAI
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 tda45/TdAI # Run inference directly in the terminal: ./llama-cli -hf tda45/TdAI
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 tda45/TdAI # Run inference directly in the terminal: ./build/bin/llama-cli -hf tda45/TdAI
Use Docker
docker model run hf.co/tda45/TdAI
- LM Studio
- Jan
- Ollama
How to use tda45/TdAI with Ollama:
ollama run hf.co/tda45/TdAI
- Unsloth Studio
How to use tda45/TdAI 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 tda45/TdAI 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 tda45/TdAI to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for tda45/TdAI to start chatting
- Atomic Chat new
- Docker Model Runner
How to use tda45/TdAI with Docker Model Runner:
docker model run hf.co/tda45/TdAI
- Lemonade
How to use tda45/TdAI with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull tda45/TdAI
Run and chat with the model
lemonade run user.TdAI-{{QUANT_TAG}}List all available models
lemonade list
| ## gguf | |
| This is a Python package for writing binary files in the [GGUF](https://github.com/ggml-org/ggml/pull/302) | |
| (GGML Universal File) format. | |
| See [convert_hf_to_gguf.py](https://github.com/ggml-org/llama.cpp/blob/master/convert_hf_to_gguf.py) | |
| as an example for its usage. | |
| ## Installation | |
| ```sh | |
| pip install gguf | |
| ``` | |
| Optionally, you can install gguf with the extra 'gui' to enable the visual GGUF editor. | |
| ```sh | |
| pip install gguf[gui] | |
| ``` | |
| ## API Examples/Simple Tools | |
| [examples/writer.py](https://github.com/ggml-org/llama.cpp/blob/master/gguf-py/examples/writer.py) β Generates `example.gguf` in the current directory to demonstrate generating a GGUF file. Note that this file cannot be used as a model. | |
| [examples/reader.py](https://github.com/ggml-org/llama.cpp/blob/master/gguf-py/examples/reader.py) β Extracts and displays key-value pairs and tensor details from a GGUF file in a readable format. | |
| [gguf/scripts/gguf_dump.py](https://github.com/ggml-org/llama.cpp/blob/master/gguf-py/gguf/scripts/gguf_dump.py) β Dumps a GGUF file's metadata to the console. | |
| [gguf/scripts/gguf_set_metadata.py](https://github.com/ggml-org/llama.cpp/blob/master/gguf-py/gguf/scripts/gguf_set_metadata.py) β Allows changing simple metadata values in a GGUF file by key. | |
| [gguf/scripts/gguf_convert_endian.py](https://github.com/ggml-org/llama.cpp/blob/master/gguf-py/gguf/scripts/gguf_convert_endian.py) β Allows converting the endianness of GGUF files. | |
| [gguf/scripts/gguf_new_metadata.py](https://github.com/ggml-org/llama.cpp/blob/master/gguf-py/gguf/scripts/gguf_new_metadata.py) β Copies a GGUF file with added/modified/removed metadata values. | |
| [gguf/scripts/gguf_editor_gui.py](https://github.com/ggml-org/llama.cpp/blob/master/gguf-py/gguf/scripts/gguf_editor_gui.py) β Allows for viewing, editing, adding, or removing metadata values within a GGUF file as well as viewing its tensors with a Qt interface. | |
| ## Development | |
| Maintainers who participate in development of this package are advised to install it in editable mode: | |
| ```sh | |
| cd /path/to/llama.cpp/gguf-py | |
| pip install --editable . | |
| ``` | |
| **Note**: This may require to upgrade your Pip installation, with a message saying that editable installation currently requires `setup.py`. | |
| In this case, upgrade Pip to the latest: | |
| ```sh | |
| pip install --upgrade pip | |
| ``` | |
| ## Automatic publishing with CI | |
| There's a GitHub workflow to make a release automatically upon creation of tags in a specified format. | |
| 1. Bump the version in `pyproject.toml`. | |
| 2. Create a tag named `gguf-vx.x.x` where `x.x.x` is the semantic version number. | |
| ```sh | |
| git tag -a gguf-v1.0.0 -m "Version 1.0 release" | |
| ``` | |
| 3. Push the tags. | |
| ```sh | |
| git push origin --tags | |
| ``` | |
| ## Manual publishing | |
| If you want to publish the package manually for any reason, you need to have `twine` and `build` installed: | |
| ```sh | |
| pip install build twine | |
| ``` | |
| Then, follow these steps to release a new version: | |
| 1. Bump the version in `pyproject.toml`. | |
| 2. Build the package: | |
| ```sh | |
| python -m build | |
| ``` | |
| 3. Upload the generated distribution archives: | |
| ```sh | |
| python -m twine upload dist/* | |
| ``` | |
| ## Run Unit Tests | |
| From root of this repository you can run this command to run all the unit tests | |
| ```bash | |
| python -m unittest discover ./gguf-py -v | |
| ``` | |
| ## TODO | |
| - [ ] Include conversion scripts as command line entry points in this package. | |