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
| static const char * ggml_backend_remoting_device_get_name(ggml_backend_dev_t dev) { | |
| virtgpu * gpu = DEV_TO_GPU(dev); | |
| // Return the prefixed name that was built once during initialization | |
| return gpu->cached_device_info.name; | |
| } | |
| static const char * ggml_backend_remoting_device_get_description(ggml_backend_dev_t dev) { | |
| virtgpu * gpu = DEV_TO_GPU(dev); | |
| // Return the pre-cached description from the virtgpu structure | |
| return gpu->cached_device_info.description; | |
| } | |
| static enum ggml_backend_dev_type ggml_backend_remoting_device_get_type(ggml_backend_dev_t dev) { | |
| virtgpu * gpu = DEV_TO_GPU(dev); | |
| return (enum ggml_backend_dev_type) gpu->cached_device_info.type; | |
| } | |
| static void ggml_backend_remoting_device_get_memory(ggml_backend_dev_t dev, size_t * free, size_t * total) { | |
| virtgpu * gpu = DEV_TO_GPU(dev); | |
| *free = gpu->cached_device_info.memory_free; | |
| *total = gpu->cached_device_info.memory_total; | |
| } | |
| static bool ggml_backend_remoting_device_supports_op(ggml_backend_dev_t dev, const ggml_tensor * op) { | |
| /* ggml-rpc cheats it like this */ | |
| /* with the current implementation of serialize_tensor, the src/view aren't properly passed */ | |
| UNUSED(dev); | |
| UNUSED(op); | |
| return true; | |
| virtgpu * gpu = DEV_TO_GPU(dev); | |
| return apir_device_supports_op(gpu, op); | |
| } | |
| static bool ggml_backend_remoting_device_supports_buft(ggml_backend_dev_t dev, ggml_backend_buffer_type_t buft) { | |
| bool supported = buft->device == dev; | |
| return supported; | |
| } | |
| static bool ggml_backend_remoting_device_offload_op(ggml_backend_dev_t dev, const ggml_tensor * op) { | |
| UNUSED(dev); | |
| UNUSED(op); | |
| return false; | |
| } | |
| static void ggml_backend_remoting_device_get_props(ggml_backend_dev_t dev, ggml_backend_dev_props * props) { | |
| props->name = ggml_backend_remoting_device_get_name(dev); | |
| props->description = ggml_backend_remoting_device_get_description(dev); | |
| props->type = ggml_backend_remoting_device_get_type(dev); | |
| ggml_backend_remoting_device_get_memory(dev, &props->memory_free, &props->memory_total); | |
| virtgpu * gpu = DEV_TO_GPU(dev); | |
| apir_device_get_props(gpu, &props->caps.async, &props->caps.host_buffer, &props->caps.buffer_from_host_ptr, | |
| &props->caps.events); | |
| props->caps.buffer_from_host_ptr = false; | |
| props->caps.async = false; | |
| props->caps.events = false; | |
| } | |
| ggml_backend_buffer_type_t ggml_backend_remoting_device_get_buffer_type(ggml_backend_dev_t dev) { | |
| virtgpu * gpu = DEV_TO_GPU(dev); | |
| static std::atomic<bool> initialized = false; | |
| static ggml_backend_buffer_type buft; | |
| if (!initialized) { | |
| static std::mutex mutex; | |
| std::lock_guard<std::mutex> lock(mutex); | |
| if (!initialized) { | |
| buft = { | |
| /* .iface = */ ggml_backend_remoting_buffer_type_interface, | |
| /* .device = */ dev, | |
| /* .context = */ (void *) gpu->cached_buffer_type.host_handle, | |
| }; | |
| initialized = true; | |
| } | |
| } | |
| return &buft; | |
| } | |
| static ggml_backend_buffer_type_t ggml_backend_remoting_device_get_buffer_from_ptr_type(ggml_backend_dev_t dev) { | |
| virtgpu * gpu = DEV_TO_GPU(dev); | |
| static std::atomic<bool> initialized = false; | |
| static ggml_backend_buffer_type buft; | |
| if (!initialized) { | |
| static std::mutex mutex; | |
| std::lock_guard<std::mutex> lock(mutex); | |
| if (!initialized) { | |
| buft = { | |
| /* .iface = */ ggml_backend_remoting_buffer_from_ptr_type_interface, | |
| /* .device = */ dev, | |
| /* .context = */ (void *) gpu->cached_buffer_type.host_handle, | |
| }; | |
| initialized = true; | |
| } | |
| } | |
| return &buft; | |
| } | |
| static ggml_backend_buffer_t ggml_backend_remoting_device_buffer_from_ptr(ggml_backend_dev_t dev, | |
| void * ptr, | |
| size_t size, | |
| size_t max_tensor_size) { | |
| virtgpu * gpu = DEV_TO_GPU(dev); | |
| ggml_backend_remoting_buffer_context * context = (ggml_backend_remoting_buffer_context *) malloc(sizeof(*context)); | |
| if (!context) { | |
| GGML_ABORT(GGML_VIRTGPU "%s: Couldn't allocate the buffer context ...", __func__); | |
| } | |
| context->gpu = gpu; | |
| context->apir_context = apir_device_buffer_from_ptr(gpu, size, max_tensor_size); | |
| context->base = ptr; | |
| context->is_from_ptr = true; | |
| ggml_backend_buffer_t buffer = | |
| ggml_backend_buffer_init(ggml_backend_remoting_device_get_buffer_from_ptr_type(dev), | |
| ggml_backend_remoting_buffer_from_ptr_interface, (void *) context, size); | |
| return buffer; | |
| } | |
| const ggml_backend_device_i ggml_backend_remoting_device_interface = { | |
| /* .get_name = */ ggml_backend_remoting_device_get_name, | |
| /* .get_description = */ ggml_backend_remoting_device_get_description, | |
| /* .get_memory = */ ggml_backend_remoting_device_get_memory, | |
| /* .get_type = */ ggml_backend_remoting_device_get_type, | |
| /* .get_props = */ ggml_backend_remoting_device_get_props, | |
| /* .init_backend = */ ggml_backend_remoting_device_init, | |
| /* .get_buffer_type = */ ggml_backend_remoting_device_get_buffer_type, | |
| /* .get_host_buffer_type = */ NULL, | |
| /* .buffer_from_host_ptr = */ ggml_backend_remoting_device_buffer_from_ptr, | |
| /* .supports_op = */ ggml_backend_remoting_device_supports_op, | |
| /* .supports_buft = */ ggml_backend_remoting_device_supports_buft, | |
| /* .offload_op = */ ggml_backend_remoting_device_offload_op, | |
| /* .event_new = */ NULL, | |
| /* .event_free = */ NULL, | |
| /* .event_synchronize = */ NULL, | |
| }; | |