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
| /** | |
| * libmtmd: A library for multimodal support in llama.cpp. | |
| * | |
| * WARNING: This API is experimental and subject to many BREAKING CHANGES. | |
| * Issues related to API usage may receive lower priority support. | |
| * | |
| * For the usage, see an example in mtmd-cli.cpp | |
| * | |
| * For contributors: | |
| * - Make sure the C API is aligned with the libllama C API (as in llama.h) | |
| * - Do not include model name (e.g., qwen, gemma) in the API, use generic terms instead | |
| * - Keep the API minimal, do not expose internal details unless necessary | |
| * | |
| * IMPORTANT: The mtmd module does NOT accept pull requests that are fully or predominantly AI-generated. | |
| * We encourage human contributors to ensure the quality and reliability of the codebase. | |
| */ | |
| extern "C" { | |
| enum mtmd_input_chunk_type { | |
| MTMD_INPUT_CHUNK_TYPE_TEXT, | |
| MTMD_INPUT_CHUNK_TYPE_IMAGE, | |
| MTMD_INPUT_CHUNK_TYPE_AUDIO, | |
| }; | |
| // opaque types | |
| struct mtmd_context; | |
| struct mtmd_bitmap; | |
| struct mtmd_image_tokens; | |
| struct mtmd_input_chunk; | |
| struct mtmd_input_chunks; | |
| struct mtmd_batch; | |
| struct mtmd_input_text { | |
| const char * text; | |
| bool add_special; | |
| bool parse_special; | |
| }; | |
| // | |
| // C API | |
| // | |
| typedef struct mtmd_context mtmd_context; | |
| typedef struct mtmd_bitmap mtmd_bitmap; | |
| typedef struct mtmd_image_tokens mtmd_image_tokens; | |
| typedef struct mtmd_input_chunk mtmd_input_chunk; | |
| typedef struct mtmd_input_chunks mtmd_input_chunks; | |
| typedef struct mtmd_input_text mtmd_input_text; | |
| typedef struct mtmd_batch mtmd_batch; | |
| typedef bool (*mtmd_progress_callback)(float progress, void * user_data); | |
| struct mtmd_context_params { | |
| bool use_gpu; | |
| bool print_timings; | |
| int n_threads; | |
| const char * image_marker; // deprecated, use media_marker instead | |
| const char * media_marker; | |
| enum llama_flash_attn_type flash_attn_type; | |
| bool warmup; // whether to run a warmup encode pass after initialization | |
| // limit number of image tokens, only for vision models with dynamic resolution | |
| int image_min_tokens; // minimum number of tokens for image input (default: read from metadata) | |
| int image_max_tokens; // maximum number of tokens for image input (default: read from metadata) | |
| // callback function passed over to mtmd proper | |
| ggml_backend_sched_eval_callback cb_eval; | |
| void * cb_eval_user_data; | |
| // batching params | |
| int32_t batch_max_tokens; // maximum number of output tokens in a batch | |
| // (note: this is not a hard-limit, the first image will always be added even if it exceeds this limit) | |
| // (default: 1024) | |
| // Called with a progress value between 0.0 and 1.0. Pass NULL to disable. | |
| // If the provided progress_callback returns true, model loading continues. | |
| // If it returns false, model loading is immediately aborted. | |
| mtmd_progress_callback progress_callback; | |
| void * progress_callback_user_data; | |
| }; | |
| MTMD_API const char * mtmd_default_marker(void); | |
| MTMD_API struct mtmd_context_params mtmd_context_params_default(void); | |
| // initialize the mtmd context | |
| // return nullptr on failure | |
| MTMD_API mtmd_context * mtmd_init_from_file(const char * mmproj_fname, | |
| const struct llama_model * text_model, | |
| const struct mtmd_context_params ctx_params); | |
| MTMD_API void mtmd_free(mtmd_context * ctx); | |
| // whether we need to set non-causal mask before llama_decode | |
| // if chunk is nullptr, we assume the default case where chunk is an image chunk | |
| MTMD_API bool mtmd_decode_use_non_causal(const mtmd_context * ctx, const mtmd_input_chunk * chunk); | |
| // whether the current model use M-RoPE for llama_decode | |
| MTMD_API bool mtmd_decode_use_mrope(const mtmd_context * ctx); | |
| // whether the current model supports vision input | |
| MTMD_API bool mtmd_support_vision(const mtmd_context * ctx); | |
| // whether the current model supports audio input | |
| MTMD_API bool mtmd_support_audio(const mtmd_context * ctx); | |
| // get audio sample rate in Hz, for example 16000 for Whisper | |
| // return -1 if audio is not supported | |
| MTMD_API int mtmd_get_audio_sample_rate(const mtmd_context * ctx); | |
| // get the current marker string | |
| MTMD_API const char * mtmd_get_marker(const mtmd_context * ctx); | |
| // mtmd_bitmap | |
| // | |
| // if bitmap is image: | |
| // length of data must be nx * ny * 3 | |
| // the data is in RGBRGBRGB... format | |
| // note: some video-capable models (i.e. qwen-vl) can merge consecutive bitmaps | |
| // into one chunk, mtmd_tokenize() will automatically handle this | |
| // if bitmap is audio: | |
| // length of data must be n_samples * sizeof(float) | |
| // the data is in float format (PCM F32) | |
| // | |
| // if data == nullptr: | |
| // the bitmap is considered "empty", and will be treated as a placeholder for counting tokens | |
| // you can pass the bitmap via mtmd_tokenize(), then call mtmd_*_get_n_tokens() to count the tokens | |
| // note: passing a placeholder bitmap to mtmd_encode() will return an error | |
| MTMD_API mtmd_bitmap * mtmd_bitmap_init (uint32_t nx, uint32_t ny, const unsigned char * data); | |
| MTMD_API mtmd_bitmap * mtmd_bitmap_init_from_audio(size_t n_samples, const float * data); | |
| MTMD_API uint32_t mtmd_bitmap_get_nx (const mtmd_bitmap * bitmap); | |
| MTMD_API uint32_t mtmd_bitmap_get_ny (const mtmd_bitmap * bitmap); | |
| MTMD_API const unsigned char * mtmd_bitmap_get_data (const mtmd_bitmap * bitmap); | |
| MTMD_API size_t mtmd_bitmap_get_n_bytes(const mtmd_bitmap * bitmap); | |
| MTMD_API bool mtmd_bitmap_is_audio (const mtmd_bitmap * bitmap); | |
| MTMD_API void mtmd_bitmap_free (mtmd_bitmap * bitmap); | |
| // bitmap ID is optional, but useful for KV cache tracking | |
| // these getters/setters are dedicated functions, so you can for example calculate the hash of the image based on mtmd_bitmap_get_data() | |
| MTMD_API const char * mtmd_bitmap_get_id(const mtmd_bitmap * bitmap); | |
| MTMD_API void mtmd_bitmap_set_id(mtmd_bitmap * bitmap, const char * id); | |
| // mtmd_bitmap lazy | |
| // | |
| // this is a special bitmap that: | |
| // - does not hold the actual data | |
| // - can be expanded into one or more chunks (either media to text chunks) | |
| // user must provide a callback to fill in the data when mtmd_tokenize() is called | |
| // this is useful for large video inputs: | |
| // - allow reading video frame by frame, without loading the entire video into memory | |
| // - allow tracking the whole video with a single ID (for example, the file hash) | |
| // set (*out_bitmap) to non-nullptr to emit a bitmap chunk; it will be freed automatically | |
| // set (*out_text) to non-nullptr to emit a text chunk; it must be heap-allocated, null-terminated and will be freed automatically | |
| // either out_bitmap or out_text can be set, but not both | |
| // out_bitmap cannot be another lazy bitmap (no nested lazy allowed) | |
| // return value: | |
| // 0 on success | |
| // -1 on EOF (signal to mtmd_tokenize to move on) | |
| // -2 on error (signal to mtmd_tokenize to abort) | |
| typedef int(* mtmd_bitmap_lazy_callback)( | |
| size_t chunk_idx, | |
| void * user_data, | |
| mtmd_bitmap ** out_bitmap, | |
| char ** out_text); | |
| MTMD_API mtmd_bitmap * mtmd_bitmap_init_lazy(mtmd_context * ctx, | |
| const char * id, // usually set to file hash | |
| void * user_data, | |
| mtmd_bitmap_lazy_callback callback); | |
| // mtmd_input_chunks | |
| // | |
| // this is simply a list of mtmd_input_chunk | |
| // the elements can only be populated via mtmd_tokenize() | |
| MTMD_API mtmd_input_chunks * mtmd_input_chunks_init(void); | |
| MTMD_API size_t mtmd_input_chunks_size(const mtmd_input_chunks * chunks); | |
| MTMD_API const mtmd_input_chunk * mtmd_input_chunks_get (const mtmd_input_chunks * chunks, size_t idx); | |
| MTMD_API void mtmd_input_chunks_free(mtmd_input_chunks * chunks); | |
| // mtmd_input_chunk | |
| // | |
| // the instance will be constructed via mtmd_tokenize() | |
| // it will be freed along with mtmd_input_chunks | |
| MTMD_API enum mtmd_input_chunk_type mtmd_input_chunk_get_type (const mtmd_input_chunk * chunk); | |
| MTMD_API const llama_token * mtmd_input_chunk_get_tokens_text (const mtmd_input_chunk * chunk, size_t * n_tokens_output); | |
| MTMD_API const mtmd_image_tokens * mtmd_input_chunk_get_tokens_image(const mtmd_input_chunk * chunk); | |
| MTMD_API size_t mtmd_input_chunk_get_n_tokens (const mtmd_input_chunk * chunk); | |
| // returns nullptr for ID on text chunk | |
| MTMD_API const char * mtmd_input_chunk_get_id (const mtmd_input_chunk * chunk); | |
| // number of temporal positions (equals to max(t,h,w) for M-RoPE; equals to n_tokens otherwise) | |
| MTMD_API llama_pos mtmd_input_chunk_get_n_pos (const mtmd_input_chunk * chunk); | |
| // in case you want to use custom logic to handle the chunk (i.e. KV cache management) | |
| // you can move the chunk ownership to your own code by copying it | |
| // remember to free the chunk when you are done with it | |
| MTMD_API mtmd_input_chunk * mtmd_input_chunk_copy(const mtmd_input_chunk * chunk); | |
| MTMD_API void mtmd_input_chunk_free(mtmd_input_chunk * chunk); | |
| // mtmd_image_tokens | |
| // | |
| // the instance will be constructed via mtmd_tokenize() | |
| // it will be freed along with mtmd_input_chunk | |
| MTMD_API size_t mtmd_image_tokens_get_n_tokens(const mtmd_image_tokens * image_tokens); // TODO: deprecate | |
| MTMD_API const char * mtmd_image_tokens_get_id (const mtmd_image_tokens * image_tokens); // TODO: deprecate | |
| // number of temporal positions (equals to max(t,h,w) for M-RoPE; equals to n_tokens otherwise) | |
| MTMD_API llama_pos mtmd_image_tokens_get_n_pos (const mtmd_image_tokens * image_tokens); // TODO: deprecate | |
| DEPRECATED(MTMD_API size_t mtmd_image_tokens_get_nx(const mtmd_image_tokens * image_tokens), | |
| "use mtmd_image_tokens_get_decoder_pos() instead"); | |
| DEPRECATED(MTMD_API size_t mtmd_image_tokens_get_ny(const mtmd_image_tokens * image_tokens), | |
| "use mtmd_image_tokens_get_decoder_pos() instead"); | |
| struct mtmd_decoder_pos { | |
| uint32_t t; | |
| uint32_t x; | |
| uint32_t y; | |
| uint32_t z; // unused for now, reserved for future use | |
| }; | |
| // get position for decoder attention, to be used by M-RoPE models | |
| // i is the index of the embedding token, ranging from 0 to mtmd_image_tokens_get_n_tokens() - 1 | |
| // pos_0 is the absolute position of the first token | |
| // return relative position (for example, embedding 0 will have position (0, 0, 0); remember to adjust it to the current absolute position) | |
| MTMD_API struct mtmd_decoder_pos mtmd_image_tokens_get_decoder_pos(const mtmd_image_tokens * image_tokens, llama_pos pos_0, size_t i); | |
| // tokenize an input text prompt and a list of bitmaps (images/audio) | |
| // the prompt must have the input image marker (default: "<__media__>") in it | |
| // the default marker is defined by mtmd_default_marker() | |
| // the marker will be replaced with the image/audio chunk | |
| // for example: | |
| // "here is an image: <__media__>\ndescribe it in detail." | |
| // this will gives 3 chunks: | |
| // 1. "here is an image: <start_of_image>" | |
| // 2. (image/audio tokens) | |
| // 3. "<end_of_image>\ndescribe it in detail." | |
| // number of bitmaps must be equal to the number of markers in the prompt | |
| // this function is thread-safe (shared ctx) | |
| // return values: | |
| // 0 on success | |
| // 1 on number of bitmaps not matching the number of markers | |
| // 2 on image preprocessing error | |
| MTMD_API int32_t mtmd_tokenize(mtmd_context * ctx, | |
| mtmd_input_chunks * output, | |
| const mtmd_input_text * text, | |
| const mtmd_bitmap ** bitmaps, | |
| size_t n_bitmaps); | |
| DEPRECATED(MTMD_API int32_t mtmd_encode(mtmd_context * ctx, const mtmd_image_tokens * image_tokens), | |
| "use mtmd_encode_chunk() instead"); | |
| // text chunk will be ignored silently, only media chunk will be encoded | |
| // returns 0 on success | |
| // returns 1 on generic error | |
| MTMD_API int32_t mtmd_encode_chunk(mtmd_context * ctx, | |
| const mtmd_input_chunk * chunk); | |
| // get output embeddings from the last encode pass | |
| // the reading size (in bytes) is equal to: | |
| // llama_model_n_embd_inp(model) * mtmd_input_chunk_get_n_tokens(chunk) * sizeof(float) | |
| MTMD_API float * mtmd_get_output_embd(mtmd_context * ctx); | |
| // batch encoding API | |
| // chunks are not owned by the batch, they will not be freed by mtmd_batch_free() | |
| // batch is valid for a given context, cannot be shared across contexts | |
| MTMD_API mtmd_batch * mtmd_batch_init(mtmd_context * ctx); | |
| MTMD_API void mtmd_batch_free(mtmd_batch * batch); | |
| // only media chunks are allowed, text chunks will be rejected | |
| // returns 0 on success | |
| // returns 1 on generic error | |
| // returns 2 if the batch is too large (chunk won't be added) | |
| // returns 3 if it cannot be batched with the existing chunks in the batch | |
| MTMD_API int32_t mtmd_batch_add_chunk(mtmd_batch * batch, const mtmd_input_chunk * chunk); | |
| // returns 0 on success | |
| // returns 1 on generic error | |
| MTMD_API int32_t mtmd_batch_encode(mtmd_batch * batch); | |
| MTMD_API float * mtmd_batch_get_output_embd(mtmd_batch * batch, const mtmd_input_chunk * chunk); | |
| // Set callback for all future logging events. | |
| // If this is not called, or NULL is supplied, everything is output on stderr. | |
| MTMD_API void mtmd_log_set(ggml_log_callback log_callback, void * user_data); | |
| // EXPERIMENTAL API to get mmproj's capabilities without initializing the full context | |
| // This is only intended to be used by llama-server, breaking changes is expected | |
| struct mtmd_caps { | |
| bool inp_vision; | |
| bool inp_audio; | |
| }; | |
| MTMD_API struct mtmd_caps mtmd_get_cap_from_file(const char * mmproj_fname); | |
| ///////////////////////////////////////// | |
| // test function, to be used in test-mtmd-c-api.c | |
| MTMD_API mtmd_input_chunks * mtmd_test_create_input_chunks(void); | |
| } // extern "C" | |
| // Get memory usage of the current model in bytes, per backend device | |
| // Note: this is an unstable API, used internally by fit_params; it WILL be removed or changed without deprecation | |
| MTMD_API std::map<ggml_backend_dev_t, size_t> mtmd_get_memory_usage( | |
| const char * mmproj_fname, | |
| struct mtmd_context_params ctx_params); | |
| // | |
| // C++ wrappers | |
| // | |
| namespace mtmd { | |
| struct mtmd_context_deleter { | |
| void operator()(mtmd_context * val) { mtmd_free(val); } | |
| }; | |
| using context_ptr = std::unique_ptr<mtmd_context, mtmd_context_deleter>; | |
| struct mtmd_bitmap_deleter { | |
| void operator()(mtmd_bitmap * val) { mtmd_bitmap_free(val); } | |
| }; | |
| using bitmap_ptr = std::unique_ptr<mtmd_bitmap, mtmd_bitmap_deleter>; | |
| struct mtmd_input_chunks_deleter { | |
| void operator()(mtmd_input_chunks * val) { mtmd_input_chunks_free(val); } | |
| }; | |
| using input_chunks_ptr = std::unique_ptr<mtmd_input_chunks, mtmd_input_chunks_deleter>; | |
| struct mtmd_input_chunk_deleter { | |
| void operator()(mtmd_input_chunk * val) { mtmd_input_chunk_free(val); } | |
| }; | |
| using input_chunk_ptr = std::unique_ptr<mtmd_input_chunk, mtmd_input_chunk_deleter>; | |
| struct mtmd_batch_deleter { | |
| void operator()(mtmd_batch * val) { mtmd_batch_free(val); } | |
| }; | |
| using batch_ptr = std::unique_ptr<mtmd_batch, mtmd_batch_deleter>; | |
| struct bitmap { | |
| bitmap_ptr ptr; | |
| bitmap() : ptr(nullptr) {} | |
| bitmap(mtmd_bitmap * bitmap) : ptr(bitmap) {} | |
| bitmap(bitmap && other) noexcept : ptr(std::move(other.ptr)) {} | |
| bitmap(uint32_t nx, uint32_t ny, const unsigned char * data) { | |
| ptr.reset(mtmd_bitmap_init(nx, ny, data)); | |
| } | |
| ~bitmap() = default; | |
| uint32_t nx() const { return mtmd_bitmap_get_nx(ptr.get()); } | |
| uint32_t ny() const { return mtmd_bitmap_get_ny(ptr.get()); } | |
| const unsigned char * data() const { return mtmd_bitmap_get_data(ptr.get()); } | |
| size_t n_bytes() const { return mtmd_bitmap_get_n_bytes(ptr.get()); } | |
| std::string id() const { return mtmd_bitmap_get_id(ptr.get()); } | |
| void set_id(const char * id) const { mtmd_bitmap_set_id(ptr.get(), id); } | |
| }; | |
| struct bitmaps { | |
| std::vector<bitmap> entries; | |
| ~bitmaps() = default; | |
| // return list of pointers to mtmd_bitmap | |
| // example: | |
| // auto bitmaps_c_ptr = bitmaps.c_ptr(); | |
| // int32_t res = mtmd_tokenize(... bitmaps_c_ptr.data(), bitmaps_c_ptr.size()); | |
| std::vector<const mtmd_bitmap *> c_ptr() { | |
| std::vector<const mtmd_bitmap *> res(entries.size()); | |
| for (size_t i = 0; i < entries.size(); i++) { | |
| res[i] = entries[i].ptr.get(); | |
| } | |
| return res; | |
| } | |
| }; | |
| struct input_chunks { | |
| input_chunks_ptr ptr; | |
| input_chunks() = default; | |
| input_chunks(mtmd_input_chunks * chunks) : ptr(chunks) {} | |
| ~input_chunks() = default; | |
| size_t size() const { return mtmd_input_chunks_size(ptr.get()); } | |
| const mtmd_input_chunk * operator[](size_t idx) const { | |
| return mtmd_input_chunks_get(ptr.get(), idx); | |
| } | |
| }; | |
| } // namespace mtmd | |