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
| /* | |
| * Copyright (c) 2023-2026 The ggml authors | |
| * | |
| * Permission is hereby granted, free of charge, to any person obtaining a copy | |
| * of this software and associated documentation files (the "Software"), to | |
| * deal in the Software without restriction, including without limitation the | |
| * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or | |
| * sell copies of the Software, and to permit persons to whom the Software is | |
| * furnished to do so, subject to the following conditions: | |
| * | |
| * The above copyright notice and this permission notice shall be included in | |
| * all copies or substantial portions of the Software. | |
| * | |
| * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR | |
| * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, | |
| * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE | |
| * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER | |
| * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING | |
| * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS | |
| * IN THE SOFTWARE. | |
| */ | |
| extern "C" { | |
| /** | |
| * @brief Maximum number of CANN devices supported. | |
| */ | |
| GGML_BACKEND_API ggml_backend_reg_t ggml_backend_cann_reg(void); | |
| /** | |
| * @brief Initializes the CANN backend for a specified device. | |
| * | |
| * This function initializes the CANN backend for the given device. | |
| * It verifies the device index, allocates a context, and creates a backend | |
| * instance. | |
| * | |
| * @param device The index of the device to initialize. | |
| * @return A pointer to the initialized backend instance, or nullptr on failure. | |
| */ | |
| GGML_BACKEND_API ggml_backend_t ggml_backend_cann_init(int32_t device); | |
| /** | |
| * @brief Checks if a given backend is a CANN backend. | |
| * | |
| * This function verifies if the provided backend is a CANN backend by comparing | |
| * its GUID with the CANN backend's GUID. | |
| * | |
| * @param backend The backend instance to check. | |
| * @return True if the backend is a CANN backend, false otherwise. | |
| */ | |
| GGML_BACKEND_API bool ggml_backend_is_cann(ggml_backend_t backend); | |
| /** | |
| * @brief Retrieves the CANN buffer type for a specified device. | |
| * | |
| * This function initializes and returns the buffer type interface associated | |
| * with the given device. It ensures thread-safe access using a mutex. | |
| * | |
| * @param device The device index for which to retrieve the buffer type. | |
| * @return A pointer to the buffer type interface for the specified device, or | |
| * nullptr if the device index is out of range. | |
| */ | |
| GGML_BACKEND_API ggml_backend_buffer_type_t | |
| ggml_backend_cann_buffer_type(int32_t device); | |
| /** | |
| * @brief Retrieves the number of CANN devices available. | |
| * | |
| * This function returns the number of CANN devices available based on | |
| * information obtained from `ggml_cann_info()`. | |
| * | |
| * @return The number of CANN devices available. | |
| */ | |
| GGML_BACKEND_API int32_t ggml_backend_cann_get_device_count(void); | |
| /** | |
| * @brief pinned host buffer for use with the CPU backend for faster copies between CPU and NPU. | |
| * | |
| * @return A pointer to the host buffer type interface. | |
| */ | |
| GGML_BACKEND_API ggml_backend_buffer_type_t ggml_backend_cann_host_buffer_type(void); | |
| /** | |
| * @brief Retrieves the description of a specific CANN device. | |
| * | |
| * This function sets the specified device, retrieves the SoC name, | |
| * and writes it into the provided description buffer. | |
| * | |
| * @param device The device index to retrieve the description for. | |
| * @param description Pointer to a buffer where the description will be written. | |
| * @param description_size Size of the description buffer. | |
| */ | |
| GGML_BACKEND_API void ggml_backend_cann_get_device_description( | |
| int32_t device, char* description, size_t description_size); | |
| /** | |
| * @brief Retrieves the memory information of a specific CANN device. | |
| * | |
| * This function sets the specified device, retrieves the free and total | |
| * memory information of the specified type (ACL_HBM_MEM), and stores them | |
| * in the provided pointers. | |
| * | |
| * @param device The device index to retrieve memory information for. | |
| * @param free Pointer to a variable where the free memory size will be stored. | |
| * @param total Pointer to a variable where the total memory size will be | |
| * stored. | |
| */ | |
| GGML_BACKEND_API void ggml_backend_cann_get_device_memory(int32_t device, | |
| size_t* free, | |
| size_t* total); | |
| } | |