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
| # ============================================================================== | |
| # ARGUMENTS | |
| # ============================================================================== | |
| # Define the CANN base image for easier version updates later | |
| ARG CHIP_TYPE=910b | |
| ARG CANN_BASE_IMAGE=quay.io/ascend/cann:8.5.0-${CHIP_TYPE}-openeuler24.03-py3.11 | |
| ARG BUILD_DATE=N/A | |
| ARG APP_VERSION=N/A | |
| ARG APP_REVISION=N/A | |
| # ============================================================================== | |
| # BUILD STAGE | |
| # Compile all binary files and libraries | |
| # ============================================================================== | |
| ARG NODE_VERSION=24 | |
| FROM docker.io/node:$NODE_VERSION AS web | |
| ARG APP_VERSION | |
| WORKDIR /app/tools/ui | |
| COPY tools/ui/package.json tools/ui/package-lock.json ./ | |
| RUN npm ci | |
| COPY tools/ui/ ./ | |
| RUN LLAMA_BUILD_NUMBER="$APP_VERSION" npm run build | |
| FROM ${CANN_BASE_IMAGE} AS build | |
| # -- Install build dependencies -- | |
| RUN yum install -y gcc g++ cmake make git openssl-devel python3 python3-pip && \ | |
| yum clean all && \ | |
| rm -rf /var/cache/yum | |
| # -- Set the working directory -- | |
| WORKDIR /app | |
| # -- Copy project files -- | |
| COPY . . | |
| COPY --from=web /app/tools/ui/dist tools/ui/dist | |
| # -- Set CANN environment variables (required for compilation) -- | |
| # Using ENV instead of `source` allows environment variables to persist across the entire image layer | |
| ENV ASCEND_TOOLKIT_HOME=/usr/local/Ascend/ascend-toolkit/latest | |
| ENV LD_LIBRARY_PATH=${ASCEND_TOOLKIT_HOME}/lib64:${LD_LIBRARY_PATH} | |
| ENV PATH=${ASCEND_TOOLKIT_HOME}/bin:${PATH} | |
| ENV ASCEND_OPP_PATH=${ASCEND_TOOLKIT_HOME}/opp | |
| ENV LD_LIBRARY_PATH=${ASCEND_TOOLKIT_HOME}/runtime/lib64/stub:$LD_LIBRARY_PATH | |
| # ... You can add other environment variables from the original file as needed ... | |
| # For brevity, only core variables are listed here. You can paste the original ENV list here. | |
| # -- Build llama.cpp -- | |
| # Use the passed CHIP_TYPE argument and add general build options | |
| ARG CHIP_TYPE | |
| RUN source /usr/local/Ascend/ascend-toolkit/set_env.sh --force \ | |
| && \ | |
| cmake -B build \ | |
| -DGGML_CANN=ON \ | |
| -DCMAKE_BUILD_TYPE=Release \ | |
| -DSOC_TYPE=ascend${CHIP_TYPE} \ | |
| -DUSE_ACL_GRAPH=ON \ | |
| . && \ | |
| cmake --build build --config Release -j$(nproc) | |
| # -- Organize build artifacts for copying in later stages -- | |
| # Create a lib directory to store all .so files | |
| RUN mkdir -p /app/lib && \ | |
| find build -name "*.so*" -exec cp -P {} /app/lib \; | |
| # Create a full directory to store all executables and Python scripts | |
| RUN mkdir -p /app/full && \ | |
| cp build/bin/* /app/full/ && \ | |
| cp *.py /app/full/ && \ | |
| cp -r conversion /app/full/ && \ | |
| cp -r gguf-py /app/full/ && \ | |
| cp -r requirements /app/full/ && \ | |
| cp requirements.txt /app/full/ | |
| # If you have a tools.sh script, make sure it is copied here | |
| # cp .devops/tools.sh /app/full/tools.sh | |
| # ============================================================================== | |
| # BASE STAGE | |
| # Create a minimal base image with CANN runtime and common libraries | |
| # ============================================================================== | |
| FROM ${CANN_BASE_IMAGE} AS base | |
| ARG BUILD_DATE=N/A | |
| ARG APP_VERSION=N/A | |
| ARG APP_REVISION=N/A | |
| ARG IMAGE_URL=https://github.com/ggml-org/llama.cpp | |
| ARG IMAGE_SOURCE=https://github.com/ggml-org/llama.cpp | |
| LABEL org.opencontainers.image.created=$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 | |
| # -- Install runtime dependencies -- | |
| RUN yum install -y libgomp curl && \ | |
| yum clean all && \ | |
| rm -rf /var/cache/yum | |
| # -- Set CANN environment variables (required for runtime) -- | |
| ENV ASCEND_TOOLKIT_HOME=/usr/local/Ascend/ascend-toolkit/latest | |
| ENV LD_LIBRARY_PATH=/app:${ASCEND_TOOLKIT_HOME}/lib64:${LD_LIBRARY_PATH} | |
| ENV PATH=${ASCEND_TOOLKIT_HOME}/bin:${PATH} | |
| ENV ASCEND_OPP_PATH=${ASCEND_TOOLKIT_HOME}/opp | |
| # ... You can add other environment variables from the original file as needed ... | |
| WORKDIR /app | |
| # Copy compiled .so files from the build stage | |
| COPY --from=build /app/lib/ /app | |
| # ============================================================================== | |
| # FINAL STAGES (TARGETS) | |
| # ============================================================================== | |
| ### Target: full | |
| # Complete image with all tools, Python bindings, and dependencies | |
| # ============================================================================== | |
| FROM base AS full | |
| COPY --from=build /app/full /app | |
| # Install Python dependencies | |
| RUN yum install -y git python3 python3-pip && \ | |
| pip3 install --no-cache-dir --upgrade pip setuptools wheel && \ | |
| pip3 install --no-cache-dir -r requirements.txt && \ | |
| yum clean all && \ | |
| rm -rf /var/cache/yum | |
| # You need to provide a tools.sh script as the entrypoint | |
| ENTRYPOINT ["/app/tools.sh"] | |
| # If there is no tools.sh, you can set the default to start the server | |
| # ENTRYPOINT ["/app/llama-server"] | |
| ### Target: light | |
| # Lightweight image containing only llama-cli and llama-completion | |
| # ============================================================================== | |
| FROM base AS light | |
| COPY --from=build /app/full/llama /app/full/llama-cli /app/full/llama-completion /app | |
| ENTRYPOINT [ "/app/llama-cli" ] | |
| ### Target: server | |
| # Dedicated server image containing only llama-server | |
| # ============================================================================== | |
| FROM base AS server | |
| ENV LLAMA_ARG_HOST=0.0.0.0 | |
| COPY --from=build /app/full/llama /app/full/llama-server /app | |
| HEALTHCHECK --interval=5m CMD [ "curl", "-f", "http://localhost:8080/health" ] | |
| ENTRYPOINT [ "/app/llama-server" ] | |