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.
- 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
- 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
- Atomic Chat
File size: 3,312 Bytes
c9c3262 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 | #pragma once
/* the rest of this file must match virglrenderer/src/apir-protocol.h */
#include <unistd.h>
#include <cstdint>
#define APIR_PROTOCOL_MAJOR 0
#define APIR_PROTOCOL_MINOR 1
#define APIR_HANDSHAKE_MAGIC 0xab1e
enum ApirCommandType {
APIR_COMMAND_TYPE_HANDSHAKE = 0,
APIR_COMMAND_TYPE_LOADLIBRARY = 1,
APIR_COMMAND_TYPE_FORWARD = 2,
APIR_COMMAND_TYPE_LENGTH = 3,
};
typedef uint64_t ApirCommandFlags;
enum ApirLoadLibraryReturnCode {
APIR_LOAD_LIBRARY_SUCCESS = 0,
// these error codes are returned by the Virglrenderer APIR component
APIR_LOAD_LIBRARY_HYPERCALL_INITIALIZATION_ERROR = 1,
APIR_LOAD_LIBRARY_ALREADY_LOADED = 2,
APIR_LOAD_LIBRARY_ENV_VAR_MISSING = 3,
APIR_LOAD_LIBRARY_CANNOT_OPEN = 4,
APIR_LOAD_LIBRARY_SYMBOL_MISSING = 5,
// any value greater than this is an APIR *backend library* initialization return code
APIR_LOAD_LIBRARY_INIT_BASE_INDEX = 6,
};
enum ApirForwardReturnCode {
APIR_FORWARD_SUCCESS = 0,
// these error codes are returned by the Virglrenderer APIR component
APIR_FORWARD_NO_DISPATCH_FCT = 1,
APIR_FORWARD_TIMEOUT = 2,
APIR_FORWARD_FAILED_TO_SYNC_STREAMS = 3,
// any value greater than this index an APIR *backend library* forward return code
APIR_FORWARD_BASE_INDEX = 4,
};
__attribute__((unused)) static inline const char * apir_command_name(ApirCommandType type) {
switch (type) {
case APIR_COMMAND_TYPE_HANDSHAKE:
return "HandShake";
case APIR_COMMAND_TYPE_LOADLIBRARY:
return "LoadLibrary";
case APIR_COMMAND_TYPE_FORWARD:
return "Forward";
default:
return "unknown";
}
}
__attribute__((unused)) static const char * apir_load_library_error(ApirLoadLibraryReturnCode code) {
#define APIR_LOAD_LIBRARY_ERROR(code_name) \
do { \
if (code == code_name) \
return #code_name; \
} while (0)
APIR_LOAD_LIBRARY_ERROR(APIR_LOAD_LIBRARY_SUCCESS);
APIR_LOAD_LIBRARY_ERROR(APIR_LOAD_LIBRARY_HYPERCALL_INITIALIZATION_ERROR);
APIR_LOAD_LIBRARY_ERROR(APIR_LOAD_LIBRARY_ALREADY_LOADED);
APIR_LOAD_LIBRARY_ERROR(APIR_LOAD_LIBRARY_ENV_VAR_MISSING);
APIR_LOAD_LIBRARY_ERROR(APIR_LOAD_LIBRARY_CANNOT_OPEN);
APIR_LOAD_LIBRARY_ERROR(APIR_LOAD_LIBRARY_SYMBOL_MISSING);
APIR_LOAD_LIBRARY_ERROR(APIR_LOAD_LIBRARY_INIT_BASE_INDEX);
return "Unknown APIR_COMMAND_TYPE_LoadLibrary error";
#undef APIR_LOAD_LIBRARY_ERROR
}
__attribute__((unused)) static const char * apir_forward_error(ApirForwardReturnCode code) {
#define APIR_FORWARD_ERROR(code_name) \
do { \
if (code == code_name) \
return #code_name; \
} while (0)
APIR_FORWARD_ERROR(APIR_FORWARD_SUCCESS);
APIR_FORWARD_ERROR(APIR_FORWARD_NO_DISPATCH_FCT);
APIR_FORWARD_ERROR(APIR_FORWARD_TIMEOUT);
APIR_FORWARD_ERROR(APIR_FORWARD_FAILED_TO_SYNC_STREAMS);
APIR_FORWARD_ERROR(APIR_FORWARD_BASE_INDEX);
return "Unknown APIR_COMMAND_TYPE_FORWARD error";
#undef APIR_FORWARD_ERROR
}
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