Instructions to use tda45/TdAI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

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

TdAI / llama.cpp /gguf-py /pyproject.toml

tda45

Upload folder using huggingface_hub (part 6)

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	[project]
	name = "gguf"
	version = "0.19.0"
	description = "Read and write ML models in GGUF for GGML"
	keywords = ["ggml", "gguf", "llama.cpp"]
	dynamic = ["classifiers"]
	readme = "README.md"
	authors = [{name = "GGML", email = "ggml@ggml.ai"}]
	requires-python = '>=3.10'
	dependencies = ['numpy (>=1.17)', 'tqdm (>=4.27)', 'pyyaml (>=5.1)', 'requests (>=2.25)']
	classifiers = [
	"Programming Language :: Python :: 3",
	"License :: OSI Approved :: MIT License",
	"Operating System :: OS Independent",
	]

	[project.urls]
	homepage = "https://ggml.ai"
	repository = "https://github.com/ggml-org/llama.cpp"

	[project.scripts]
	gguf-convert-endian = "gguf.scripts.gguf_convert_endian:main"
	gguf-dump = "gguf.scripts.gguf_dump:main"
	gguf-set-metadata = "gguf.scripts.gguf_set_metadata:main"
	gguf-new-metadata = "gguf.scripts.gguf_new_metadata:main"
	gguf-editor-gui = "gguf.scripts.gguf_editor_gui:main"

	[project.optional-dependencies]
	gui = ['PySide6 (>=6.9,<7.0) ; python_version >= "3.9" and python_version < "3.14"']

	[tool.poetry]
	packages = [
	{include = "gguf"},
	{include = "gguf/py.typed"},
	]

	[tool.poetry.dependencies]
	python = ">=3.10"

	[tool.poetry.group.dev.dependencies]
	pytest = "^5.2"

	[build-system]
	requires = ["poetry-core>=1.0.0"]
	build-backend = "poetry.core.masonry.api"