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
| ARG GCC_VERSION=15.2.0 | |
| ARG UBUNTU_VERSION=24.04 | |
| ARG BUILD_DATE=N/A | |
| ARG APP_VERSION=N/A | |
| ARG APP_REVISION=N/A | |
| ### Build Llama.cpp stage | |
| FROM docker.io/gcc:${GCC_VERSION} AS build | |
| RUN --mount=type=cache,target=/var/cache/apt,sharing=locked \ | |
| --mount=type=cache,target=/var/lib/apt/lists,sharing=locked \ | |
| apt update -y && \ | |
| apt upgrade -y && \ | |
| apt install -y --no-install-recommends \ | |
| git cmake ccache ninja-build \ | |
| # WARNING: Do not use libopenblas-openmp-dev. libopenblas-dev is faster. | |
| libopenblas-dev libssl-dev && \ | |
| rm -rf /var/lib/apt/lists/* | |
| WORKDIR /app | |
| COPY . . | |
| RUN --mount=type=cache,target=/root/.ccache \ | |
| --mount=type=cache,target=/app/build \ | |
| cmake -S . -B build -G Ninja \ | |
| -DCMAKE_BUILD_TYPE=Release \ | |
| -DCMAKE_C_COMPILER_LAUNCHER=ccache \ | |
| -DCMAKE_CXX_COMPILER_LAUNCHER=ccache \ | |
| -DLLAMA_BUILD_TESTS=OFF \ | |
| -DGGML_NATIVE=OFF \ | |
| -DGGML_BACKEND_DL=ON \ | |
| -DGGML_CPU_ALL_VARIANTS=ON \ | |
| -DGGML_BLAS=ON \ | |
| -DGGML_BLAS_VENDOR=OpenBLAS && \ | |
| cmake --build build --config Release -j $(nproc) && \ | |
| cmake --install build --prefix /opt/llama.cpp | |
| COPY *.py /opt/llama.cpp/bin | |
| COPY .devops/tools.sh /opt/llama.cpp/bin | |
| COPY conversion /opt/llama.cpp/conversion | |
| COPY gguf-py /opt/llama.cpp/gguf-py | |
| COPY requirements.txt /opt/llama.cpp/gguf-py | |
| COPY requirements /opt/llama.cpp/gguf-py/requirements | |
| ### Collect all llama.cpp binaries, libraries and distro libraries | |
| FROM scratch AS collector | |
| # Copy llama.cpp binaries and libraries | |
| COPY --from=build /opt/llama.cpp/bin /llama.cpp/bin | |
| COPY --from=build /opt/llama.cpp/lib /llama.cpp/lib | |
| COPY --from=build /opt/llama.cpp/gguf-py /llama.cpp/gguf-py | |
| COPY --from=build /opt/llama.cpp/conversion /llama.cpp/conversion | |
| ### Base image | |
| FROM docker.io/ubuntu:${UBUNTU_VERSION} AS base | |
| ARG BUILD_DATE=N/A | |
| ARG APP_VERSION=N/A | |
| ARG APP_REVISION=N/A | |
| ARG IMAGE_URL=https://github.com/ggml-org/llama.cpp | |
| ARG IMAGE_SOURCE=https://github.com/ggml-org/llama.cpp | |
| LABEL org.opencontainers.image.created=$BUILD_DATE \ | |
| org.opencontainers.image.version=$APP_VERSION \ | |
| org.opencontainers.image.revision=$APP_REVISION \ | |
| org.opencontainers.image.title="llama.cpp" \ | |
| org.opencontainers.image.description="LLM inference in C/C++" \ | |
| org.opencontainers.image.url=$IMAGE_URL \ | |
| org.opencontainers.image.source=$IMAGE_SOURCE | |
| RUN --mount=type=cache,target=/var/cache/apt,sharing=locked \ | |
| --mount=type=cache,target=/var/lib/apt/lists,sharing=locked \ | |
| apt update -y && \ | |
| apt install -y --no-install-recommends \ | |
| # WARNING: Do not use libopenblas-openmp-dev. libopenblas-dev is faster. | |
| # See: https://github.com/ggml-org/llama.cpp/pull/15915#issuecomment-3317166506 | |
| curl libgomp1 libopenblas-dev && \ | |
| apt autoremove -y && \ | |
| apt clean -y && \ | |
| rm -rf /tmp/* /var/tmp/* && \ | |
| find /var/cache/apt/archives /var/lib/apt/lists -not -name lock -type f -delete && \ | |
| find /var/cache -type f -delete | |
| # Copy llama.cpp libraries | |
| COPY --from=collector /llama.cpp/lib /usr/lib/s390x-linux-gnu | |
| ### Full | |
| FROM base AS full | |
| ENV PATH="/root/.cargo/bin:${PATH}" | |
| WORKDIR /app | |
| RUN --mount=type=cache,target=/var/cache/apt,sharing=locked \ | |
| --mount=type=cache,target=/var/lib/apt/lists,sharing=locked \ | |
| apt update -y && \ | |
| apt install -y \ | |
| git cmake libjpeg-dev \ | |
| python3 python3-pip python3-dev && \ | |
| apt autoremove -y && \ | |
| apt clean -y && \ | |
| rm -rf /tmp/* /var/tmp/* && \ | |
| find /var/cache/apt/archives /var/lib/apt/lists -not -name lock -type f -delete && \ | |
| find /var/cache -type f -delete | |
| RUN curl https://sh.rustup.rs -sSf | bash -s -- -y | |
| COPY --from=collector /llama.cpp/bin /app | |
| COPY --from=collector /llama.cpp/gguf-py /app/gguf-py | |
| COPY --from=collector /llama.cpp/conversion /app/conversion | |
| RUN pip install --no-cache-dir --break-system-packages \ | |
| -r /app/gguf-py/requirements.txt | |
| ENTRYPOINT [ "/app/tools.sh" ] | |
| ### CLI Only | |
| FROM base AS light | |
| WORKDIR /llama.cpp/bin | |
| # Copy llama.cpp binaries and libraries | |
| COPY --from=collector /llama.cpp/bin/*.so /llama.cpp/bin | |
| COPY --from=collector /llama.cpp/bin/llama /llama.cpp/bin/llama-cli /llama.cpp/bin/llama-completion /llama.cpp/bin | |
| ENTRYPOINT [ "/llama.cpp/bin/llama-cli" ] | |
| ### Server | |
| FROM base AS server | |
| ENV LLAMA_ARG_HOST=0.0.0.0 | |
| WORKDIR /llama.cpp/bin | |
| # Copy llama.cpp binaries and libraries | |
| COPY --from=collector /llama.cpp/bin/*.so /llama.cpp/bin | |
| COPY --from=collector /llama.cpp/bin/llama /llama.cpp/bin/llama-server /llama.cpp/bin | |
| EXPOSE 8080 | |
| ENTRYPOINT [ "/llama.cpp/bin/llama-server" ] | |