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
| template <typename T> | |
| T neg_infinity() { | |
| return -std::numeric_limits<T>::infinity(); | |
| } | |
| template<typename T_Dst, typename T_Src = T_Dst> | |
| struct typed_data { | |
| const T_Src * src; | |
| T_Dst * dst; | |
| }; | |
| template<typename T_Dst, typename T_Src = T_Dst> | |
| typed_data<T_Dst, T_Src> cast_data(ggml_tensor * dst) { | |
| return { | |
| /* .src = */ static_cast<const T_Src *>(dst->src[0]->data), | |
| /* .dst = */ static_cast<T_Dst *>(dst->data) | |
| }; | |
| } | |
| const float GELU_QUICK_COEF = -1.702f; | |
| void ggml_sycl_sqrt(ggml_backend_sycl_context & ctx, ggml_tensor * dst); | |
| void ggml_sycl_sin(ggml_backend_sycl_context & ctx, ggml_tensor * dst); | |
| void ggml_sycl_cos(ggml_backend_sycl_context & ctx, ggml_tensor * dst); | |
| void ggml_sycl_acc(ggml_backend_sycl_context & ctx, ggml_tensor * dst); | |
| void ggml_sycl_gelu(ggml_backend_sycl_context & ctx, ggml_tensor * dst); | |
| void ggml_sycl_silu(ggml_backend_sycl_context & ctx, ggml_tensor * dst); | |
| void ggml_sycl_gelu_quick(ggml_backend_sycl_context & ctx, ggml_tensor * dst); | |
| void ggml_sycl_swiglu_oai(ggml_backend_sycl_context & ctx, ggml_tensor * dst); | |
| void ggml_sycl_gelu_erf(ggml_backend_sycl_context & ctx, ggml_tensor * dst); | |
| void ggml_sycl_tanh(ggml_backend_sycl_context & ctx, ggml_tensor * dst); | |
| void ggml_sycl_relu(ggml_backend_sycl_context & ctx, ggml_tensor * dst); | |
| void ggml_sycl_sigmoid(ggml_backend_sycl_context & ctx, ggml_tensor * dst); | |
| void ggml_sycl_hardsigmoid(ggml_backend_sycl_context & ctx, ggml_tensor * dst); | |
| void ggml_sycl_hardswish(ggml_backend_sycl_context & ctx, ggml_tensor * dst); | |
| void ggml_sycl_exp(ggml_backend_sycl_context & ctx, ggml_tensor * dst); | |
| void ggml_sycl_expm1(ggml_backend_sycl_context & ctx, ggml_tensor * dst); | |
| void ggml_sycl_log(ggml_backend_sycl_context & ctx, ggml_tensor * dst); | |
| void ggml_sycl_softplus(ggml_backend_sycl_context & ctx, ggml_tensor * dst); | |
| void ggml_sycl_neg(ggml_backend_sycl_context & ctx, ggml_tensor * dst); | |
| void ggml_sycl_step(ggml_backend_sycl_context & ctx, ggml_tensor * dst); | |
| void ggml_sycl_leaky_relu(ggml_backend_sycl_context & ctx, ggml_tensor * dst); | |
| void ggml_sycl_sqr(ggml_backend_sycl_context & ctx, ggml_tensor * dst); | |
| void ggml_sycl_clamp(ggml_backend_sycl_context & ctx, ggml_tensor * dst); | |
| void ggml_sycl_sgn(ggml_backend_sycl_context & ctx, ggml_tensor * dst); | |
| void ggml_sycl_abs(ggml_backend_sycl_context & ctx, ggml_tensor * dst); | |
| void ggml_sycl_elu(ggml_backend_sycl_context & ctx, ggml_tensor * dst); | |
| void ggml_sycl_geglu(ggml_backend_sycl_context & ctx, ggml_tensor * dst); | |
| void ggml_sycl_reglu(ggml_backend_sycl_context & ctx, ggml_tensor * dst); | |
| void ggml_sycl_swiglu(ggml_backend_sycl_context & ctx, ggml_tensor * dst); | |
| void ggml_sycl_geglu_erf(ggml_backend_sycl_context & ctx, ggml_tensor * dst); | |
| void ggml_sycl_geglu_quick(ggml_backend_sycl_context & ctx, ggml_tensor * dst); | |
| void ggml_sycl_floor(ggml_backend_sycl_context & ctx, ggml_tensor * dst); | |
| void ggml_sycl_ceil(ggml_backend_sycl_context & ctx, ggml_tensor * dst); | |
| void ggml_sycl_round(ggml_backend_sycl_context & ctx, ggml_tensor * dst); | |
| void ggml_sycl_trunc(ggml_backend_sycl_context & ctx, ggml_tensor * dst); | |
| void ggml_sycl_arange(ggml_backend_sycl_context & ctx, ggml_tensor * dst); | |