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 { isSvgMimeType, svgBase64UrlToPngDataURL } from './svg-to-png'; | |
| import { isWebpMimeType, webpBase64UrlToPngDataURL } from './webp-to-png'; | |
| import { heicFileToJpegDataURL, isHeicMimeType } from './heic-to-jpeg'; | |
| import { FileTypeCategory } from '$lib/enums'; | |
| import { SETTINGS_KEYS } from '$lib/constants'; | |
| import { modelsStore } from '$lib/stores/models.svelte'; | |
| import { settingsStore } from '$lib/stores/settings.svelte'; | |
| import { toast } from 'svelte-sonner'; | |
| import { getFileTypeCategory } from '$lib/utils'; | |
| import { convertPDFToText } from './pdf-processing'; | |
| /** | |
| * Read a file as a data URL (base64 encoded) | |
| * @param file - The file to read | |
| * @returns Promise resolving to the data URL string | |
| */ | |
| function readFileAsDataURL(file: File): Promise<string> { | |
| return new Promise((resolve, reject) => { | |
| const reader = new FileReader(); | |
| reader.onload = () => resolve(reader.result as string); | |
| reader.onerror = () => reject(reader.error); | |
| reader.readAsDataURL(file); | |
| }); | |
| } | |
| /** | |
| * Read a file as UTF-8 text | |
| * @param file - The file to read | |
| * @returns Promise resolving to the text content | |
| */ | |
| function readFileAsUTF8(file: File): Promise<string> { | |
| return new Promise((resolve, reject) => { | |
| const reader = new FileReader(); | |
| reader.onload = () => resolve(reader.result as string); | |
| reader.onerror = () => reject(reader.error); | |
| reader.readAsText(file); | |
| }); | |
| } | |
| /** | |
| * Process uploaded files into ChatUploadedFile format with previews and content | |
| * | |
| * This function processes various file types and generates appropriate previews: | |
| * - Images: Base64 data URLs with format normalization (SVG/WebP → PNG) | |
| * - Text files: UTF-8 content extraction | |
| * - PDFs: Metadata only (processed later in conversion pipeline) | |
| * - Audio: Base64 data URLs for preview | |
| * | |
| * @param files - Array of File objects to process | |
| * @returns Promise resolving to array of ChatUploadedFile objects | |
| */ | |
| export async function processFilesToChatUploaded( | |
| files: File[], | |
| activeModelId?: string | |
| ): Promise<ChatUploadedFile[]> { | |
| const results: ChatUploadedFile[] = []; | |
| for (const file of files) { | |
| const id = Date.now().toString() + Math.random().toString(36).substr(2, 9); | |
| const base: ChatUploadedFile = { | |
| id, | |
| name: file.name, | |
| size: file.size, | |
| type: file.type, | |
| file | |
| }; | |
| try { | |
| if (getFileTypeCategory(file.type) === FileTypeCategory.IMAGE) { | |
| let preview = await readFileAsDataURL(file); | |
| // Normalize SVG and WebP to PNG, and HEIC to compressed JPEG, in previews | |
| if (isSvgMimeType(file.type)) { | |
| try { | |
| preview = await svgBase64UrlToPngDataURL(preview); | |
| } catch (err) { | |
| console.error('Failed to convert SVG to PNG:', err); | |
| } | |
| } else if (isWebpMimeType(file.type)) { | |
| try { | |
| preview = await webpBase64UrlToPngDataURL(preview); | |
| } catch (err) { | |
| console.error('Failed to convert WebP to PNG:', err); | |
| } | |
| } else if (isHeicMimeType(file.type)) { | |
| try { | |
| preview = await heicFileToJpegDataURL(file); | |
| } catch (err) { | |
| console.error('Failed to convert HEIC to PNG:', err); | |
| continue; | |
| } | |
| } | |
| results.push({ ...base, preview }); | |
| } else if (getFileTypeCategory(file.type) === FileTypeCategory.PDF) { | |
| // Extract text content from PDF for preview | |
| try { | |
| const textContent = await convertPDFToText(file); | |
| results.push({ ...base, textContent }); | |
| } catch (err) { | |
| console.warn('Failed to extract text from PDF, adding without content:', err); | |
| results.push(base); | |
| } | |
| // Show suggestion toast if vision model is available but PDF as image is disabled | |
| const hasVisionSupport = activeModelId | |
| ? modelsStore.modelSupportsVision(activeModelId) | |
| : false; | |
| const currentConfig = settingsStore.config; | |
| if (hasVisionSupport && !currentConfig.pdfAsImage) { | |
| toast.info(`You can enable parsing PDF as images with vision models.`, { | |
| duration: 8000, | |
| action: { | |
| label: 'Enable PDF as Images', | |
| onClick: () => { | |
| settingsStore.updateConfig(SETTINGS_KEYS.PDF_AS_IMAGE, true); | |
| toast.success('PDF parsing as images enabled!', { | |
| duration: 3000 | |
| }); | |
| } | |
| } | |
| }); | |
| } | |
| } else if (getFileTypeCategory(file.type) === FileTypeCategory.AUDIO) { | |
| // Generate preview URL for audio files | |
| const preview = await readFileAsDataURL(file); | |
| results.push({ ...base, preview }); | |
| } else if (getFileTypeCategory(file.type) === FileTypeCategory.VIDEO) { | |
| // Generate preview URL for video files | |
| const preview = await readFileAsDataURL(file); | |
| results.push({ ...base, preview }); | |
| } else { | |
| // Fallback: treat unknown files as text | |
| try { | |
| const textContent = await readFileAsUTF8(file); | |
| results.push({ ...base, textContent }); | |
| } catch (err) { | |
| console.warn('Failed to read file as text, adding without content:', err); | |
| results.push(base); | |
| } | |
| } | |
| } catch (error) { | |
| console.error('Error processing file', file.name, error); | |
| results.push(base); | |
| } | |
| } | |
| return results; | |
| } | |