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
| set(TARGET llama-eval-callback) | |
| add_executable(${TARGET} eval-callback.cpp) | |
| install(TARGETS ${TARGET} RUNTIME) | |
| target_link_libraries(${TARGET} PRIVATE llama-common llama ${CMAKE_THREAD_LIBS_INIT}) | |
| target_compile_features(${TARGET} PRIVATE cxx_std_17) | |
| if(LLAMA_BUILD_TESTS) | |
| if(NOT ${CMAKE_SYSTEM_PROCESSOR} MATCHES "s390x") | |
| set(MODEL_NAME "tinyllamas/stories15M-q4_0.gguf") | |
| set(MODEL_HASH "SHA256=66967fbece6dbe97886593fdbb73589584927e29119ec31f08090732d1861739") | |
| else() | |
| set(MODEL_NAME "tinyllamas/stories15M-be.Q4_0.gguf") | |
| set(MODEL_HASH "SHA256=9aec857937849d976f30397e97eb1cabb53eb9dcb1ce4611ba8247fb5f44c65d") | |
| endif() | |
| set(MODEL_DEST "${CMAKE_BINARY_DIR}/${MODEL_NAME}") | |
| set(TEST_TARGET test-eval-callback) | |
| add_test(NAME ${TEST_TARGET}-download-model COMMAND ${CMAKE_COMMAND} | |
| -DDEST=${MODEL_DEST} | |
| -DNAME=${MODEL_NAME} | |
| -DHASH=${MODEL_HASH} | |
| -P ${CMAKE_SOURCE_DIR}/cmake/download-models.cmake | |
| ) | |
| set_tests_properties(${TEST_TARGET}-download-model PROPERTIES FIXTURES_SETUP ${TEST_TARGET}-download-model) | |
| add_test(NAME ${TEST_TARGET} COMMAND llama-eval-callback -m "${MODEL_DEST}" --prompt hello --seed 42 -ngl 0) | |
| set_tests_properties(${TEST_TARGET} PROPERTIES FIXTURES_REQUIRED ${TEST_TARGET}-download-model) | |
| endif() | |