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
| import { page } from '$app/state'; | |
| import { AttachmentAction } from '$lib/enums'; | |
| export interface AttachmentModalityFlags { | |
| hasVisionModality: boolean; | |
| hasAudioModality: boolean; | |
| hasVideoModality: boolean; | |
| hasMcpPromptsSupport: boolean; | |
| hasMcpResourcesSupport: boolean; | |
| } | |
| export interface AttachmentActionCallbacks { | |
| onFileUpload?: () => void; | |
| onSystemPromptClick?: () => void; | |
| onMcpPromptClick?: () => void; | |
| onMcpResourcesClick?: () => void; | |
| } | |
| export interface UseAttachmentMenuReturn { | |
| readonly callbacks: Record<string, () => void>; | |
| isItemEnabled(enabledWhen: string | undefined): boolean; | |
| isItemVisible(visibleWhen: string | undefined): boolean; | |
| getSystemMessageTooltip(): string; | |
| } | |
| /** | |
| * useAttachmentMenu - Shared logic for attachment menu components. | |
| * | |
| * Encapsulates the modality-flag checks and callback wrapping that is | |
| * identical across the desktop dropdown (`ChatFormActionAddDropdown`) | |
| * and the mobile sheet (`ChatFormActionAddSheet`). | |
| * | |
| * @param getFlags - Getter returning the current modality capability flags. | |
| * @param getCallbacks - Getter returning the raw action callbacks from props. | |
| * @param close - Function that dismisses the hosting UI element (dropdown / sheet). | |
| */ | |
| export function useAttachmentMenu( | |
| getFlags: () => AttachmentModalityFlags, | |
| getCallbacks: () => AttachmentActionCallbacks, | |
| close: () => void | |
| ): UseAttachmentMenuReturn { | |
| const modalityFlags = $derived(getFlags()); | |
| const callbacks = $derived.by(() => { | |
| const cbs = getCallbacks(); | |
| const wrap = (fn?: () => void) => () => { | |
| close(); | |
| fn?.(); | |
| }; | |
| return { | |
| [AttachmentAction.FILE_UPLOAD]: wrap(cbs.onFileUpload), | |
| [AttachmentAction.SYSTEM_PROMPT_CLICK]: wrap(cbs.onSystemPromptClick), | |
| [AttachmentAction.MCP_PROMPT_CLICK]: wrap(cbs.onMcpPromptClick), | |
| [AttachmentAction.MCP_RESOURCES_CLICK]: wrap(cbs.onMcpResourcesClick) | |
| }; | |
| }); | |
| function isItemEnabled(enabledWhen: string | undefined): boolean { | |
| if (!enabledWhen || enabledWhen === 'always') return true; | |
| return !!modalityFlags[enabledWhen as keyof AttachmentModalityFlags]; | |
| } | |
| function isItemVisible(visibleWhen: string | undefined): boolean { | |
| if (!visibleWhen) return true; | |
| return !!modalityFlags[visibleWhen as keyof AttachmentModalityFlags]; | |
| } | |
| function getSystemMessageTooltip(): string { | |
| return !page.params.id | |
| ? 'Add custom system message for a new conversation' | |
| : 'Inject custom system message at the beginning of the conversation'; | |
| } | |
| return { | |
| get callbacks() { | |
| return callbacks; | |
| }, | |
| isItemEnabled, | |
| isItemVisible, | |
| getSystemMessageTooltip | |
| }; | |
| } | |