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
| namespace ov { | |
| namespace frontend { | |
| namespace ggml { | |
| class GgmlDecoder : public DecoderBase { | |
| public: | |
| virtual ov::Any get_attribute(const std::string & name) const = 0; | |
| virtual PartialShape get_input_shape(int node_idx, const std::string & name) const = 0; | |
| virtual std::vector<size_t> get_input_stride(int node_idx, const std::string & name) const = 0; | |
| virtual size_t get_view_input_size(int node_idx, const std::string & name) const = 0; | |
| virtual size_t get_view_input_offset(int node_idx, const std::string & name, size_t view_index) const = 0; | |
| virtual size_t get_view_input_src_offset(int node_idx, const std::string & name, size_t view_index) const = 0; | |
| virtual std::vector<size_t> get_view_input_stride(int node_idx, | |
| const std::string & name, | |
| size_t view_index) const = 0; | |
| virtual std::vector<size_t> get_view_input_src_stride(int node_idx, | |
| const std::string & name, | |
| size_t view_index) const = 0; | |
| virtual Shape get_view_input_ggml_shape(int node_idx, const std::string & name, size_t view_index) const = 0; | |
| virtual Shape get_view_input_src_ggml_shape(int node_idx, const std::string & name, size_t view_index) const = 0; | |
| virtual PartialShape get_view_input_ov_shape(int node_idx, const std::string & name, size_t view_index) const = 0; | |
| virtual PartialShape get_view_input_src_ov_shape(int node_idx, | |
| const std::string & name, | |
| size_t view_index) const = 0; | |
| virtual std::string get_view_input_name(int node_idx, const std::string & name, size_t view_index) const = 0; | |
| virtual std::string get_view_input_src_name(int node_idx, const std::string & name, size_t view_index) const = 0; | |
| virtual element::Type get_input_type(int node_idx, const std::string & name) const = 0; | |
| virtual size_t get_input_size() const = 0; | |
| virtual size_t get_input_size(int node_idx) const = 0; | |
| virtual void get_input_node(size_t input_port_idx, | |
| std::string & producer_name, | |
| std::string & producer_output_port_name, | |
| size_t & producer_output_port_index) const = 0; | |
| virtual std::vector<std::string> get_input_names(int node_idx) const = 0; | |
| virtual PartialShape get_output_shape(int node_idx) const = 0; | |
| virtual element::Type get_output_type(const int node_idx) const = 0; | |
| virtual std::vector<size_t> get_output_stride(int node_idx) const = 0; | |
| virtual int32_t * get_input_op_params(int node_idx, const std::string & name) const = 0; | |
| virtual int32_t * get_output_op_params(int node_idx) const = 0; | |
| virtual size_t get_output_op_offset(int node_idx) const = 0; | |
| virtual std::vector<std::string> get_output_names(int node_idx) const = 0; | |
| virtual const std::string & get_op_type() const = 0; | |
| virtual const std::string & get_op_type(int node_idx) const = 0; | |
| virtual const std::string & get_op_name() const = 0; | |
| virtual const std::string & get_op_name(int node_idx) const = 0; | |
| virtual void visit_subgraph(std::function<void(std::shared_ptr<GgmlDecoder>, int node_idx)> node_visitor) const = 0; | |
| virtual int get_op_case(int node_idx) const = 0; | |
| virtual const std::map<std::string, std::shared_ptr<ov::Node>> & get_model_inputs() const = 0; | |
| virtual const std::map<std::string, std::shared_ptr<ov::Node>> & get_model_extra_inputs() const = 0; | |
| virtual const std::map<std::string, std::shared_ptr<ov::Node>> & get_model_weights() const = 0; | |
| virtual std::vector<std::string> get_model_output_names() const = 0; | |
| virtual int32_t * get_rope_params() const = 0; | |
| virtual bool has_mixed_rope_params() const = 0; | |
| virtual std::map<std::string, std::string> get_kv_param_res_names() const = 0; | |
| virtual bool is_static() const = 0; | |
| virtual bool is_stateful() const = 0; | |
| virtual bool is_splited_model() const = 0; | |
| virtual int is_swa_layer(int layer) const = 0; | |
| virtual int32_t get_op_dynamic_dim(int node_idx) const = 0; | |
| }; | |
| } // namespace ggml | |
| } // namespace frontend | |
| } // namespace ov | |