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
| <script lang="ts"> | |
| import { Button } from '$lib/components/ui/button'; | |
| import { Checkbox } from '$lib/components/ui/checkbox'; | |
| import SearchInput from '$lib/components/app/forms/SearchInput.svelte'; | |
| import { ScrollArea } from '$lib/components/ui/scroll-area'; | |
| import { SvelteSet } from 'svelte/reactivity'; | |
| interface Props { | |
| conversations: DatabaseConversation[]; | |
| messageCountMap?: Map<string, number>; | |
| mode: 'export' | 'import'; | |
| onCancel: () => void; | |
| onConfirm: (selectedConversations: DatabaseConversation[]) => void; | |
| } | |
| let { conversations, messageCountMap = new Map(), mode, onCancel, onConfirm }: Props = $props(); | |
| let searchQuery = $state(''); | |
| let selectedIds = $state.raw<SvelteSet<string>>(getInitialSelectedIds()); | |
| let lastClickedId = $state<string | null>(null); | |
| function getInitialSelectedIds(): SvelteSet<string> { | |
| return new SvelteSet(conversations.map((c) => c.id)); | |
| } | |
| let filteredConversations = $derived( | |
| conversations.filter((conv) => { | |
| const name = conv.name || 'Untitled conversation'; | |
| return name.toLowerCase().includes(searchQuery.toLowerCase()); | |
| }) | |
| ); | |
| let allSelected = $derived( | |
| filteredConversations.length > 0 && | |
| filteredConversations.every((conv) => selectedIds.has(conv.id)) | |
| ); | |
| let someSelected = $derived( | |
| filteredConversations.some((conv) => selectedIds.has(conv.id)) && !allSelected | |
| ); | |
| function toggleConversation(id: string, shiftKey: boolean = false) { | |
| const newSet = new SvelteSet(selectedIds); | |
| if (shiftKey && lastClickedId !== null) { | |
| const lastIndex = filteredConversations.findIndex((c) => c.id === lastClickedId); | |
| const currentIndex = filteredConversations.findIndex((c) => c.id === id); | |
| if (lastIndex !== -1 && currentIndex !== -1) { | |
| const start = Math.min(lastIndex, currentIndex); | |
| const end = Math.max(lastIndex, currentIndex); | |
| const shouldSelect = !newSet.has(id); | |
| for (let i = start; i <= end; i++) { | |
| if (shouldSelect) { | |
| newSet.add(filteredConversations[i].id); | |
| } else { | |
| newSet.delete(filteredConversations[i].id); | |
| } | |
| } | |
| selectedIds = newSet; | |
| return; | |
| } | |
| } | |
| if (newSet.has(id)) { | |
| newSet.delete(id); | |
| } else { | |
| newSet.add(id); | |
| } | |
| selectedIds = newSet; | |
| lastClickedId = id; | |
| } | |
| function toggleAll() { | |
| if (allSelected) { | |
| const newSet = new SvelteSet(selectedIds); | |
| filteredConversations.forEach((conv) => newSet.delete(conv.id)); | |
| selectedIds = newSet; | |
| } else { | |
| const newSet = new SvelteSet(selectedIds); | |
| filteredConversations.forEach((conv) => newSet.add(conv.id)); | |
| selectedIds = newSet; | |
| } | |
| } | |
| function handleConfirm() { | |
| const selected = conversations.filter((conv) => selectedIds.has(conv.id)); | |
| onConfirm(selected); | |
| } | |
| function handleCancel() { | |
| selectedIds = getInitialSelectedIds(); | |
| searchQuery = ''; | |
| lastClickedId = null; | |
| onCancel(); | |
| } | |
| export function reset() { | |
| selectedIds = getInitialSelectedIds(); | |
| searchQuery = ''; | |
| lastClickedId = null; | |
| } | |
| </script> | |
| <div class="space-y-4"> | |
| <SearchInput bind:value={searchQuery} placeholder="Search conversations..." /> | |
| <div class="flex items-center justify-between text-sm text-muted-foreground"> | |
| <span> | |
| {selectedIds.size} of {conversations.length} selected | |
| {#if searchQuery} | |
| ({filteredConversations.length} shown) | |
| {/if} | |
| </span> | |
| </div> | |
| <div class="overflow-hidden rounded-md border"> | |
| <ScrollArea class="h-[400px]"> | |
| <table class="w-full"> | |
| <thead class="sticky top-0 z-10 bg-muted"> | |
| <tr class="border-b"> | |
| <th class="w-12 p-3 text-left"> | |
| <Checkbox | |
| checked={allSelected} | |
| indeterminate={someSelected} | |
| onCheckedChange={toggleAll} | |
| /> | |
| </th> | |
| <th class="p-3 text-left text-sm font-medium">Conversation Name</th> | |
| <th class="w-32 p-3 text-left text-sm font-medium">Messages</th> | |
| </tr> | |
| </thead> | |
| <tbody> | |
| {#if filteredConversations.length === 0} | |
| <tr> | |
| <td colspan="3" class="p-8 text-center text-sm text-muted-foreground"> | |
| {#if searchQuery} | |
| No conversations found matching "{searchQuery}" | |
| {:else} | |
| No conversations available | |
| {/if} | |
| </td> | |
| </tr> | |
| {:else} | |
| {#each filteredConversations as conv (conv.id)} | |
| <tr | |
| class="cursor-pointer border-b transition-colors hover:bg-muted/50" | |
| onclick={(event) => toggleConversation(conv.id, event.shiftKey)} | |
| > | |
| <td class="p-3"> | |
| <Checkbox | |
| checked={selectedIds.has(conv.id)} | |
| onclick={(event) => { | |
| event.preventDefault(); | |
| event.stopPropagation(); | |
| toggleConversation(conv.id, event.shiftKey); | |
| }} | |
| /> | |
| </td> | |
| <td class="p-3 text-sm"> | |
| <div class="max-w-[17rem] truncate" title={conv.name || 'Untitled conversation'}> | |
| {conv.name || 'Untitled conversation'} | |
| </div> | |
| </td> | |
| <td class="p-3 text-sm text-muted-foreground"> | |
| {messageCountMap.get(conv.id) ?? 0} | |
| </td> | |
| </tr> | |
| {/each} | |
| {/if} | |
| </tbody> | |
| </table> | |
| </ScrollArea> | |
| </div> | |
| <div class="flex justify-end gap-2"> | |
| <Button variant="outline" onclick={handleCancel}>Cancel</Button> | |
| <Button onclick={handleConfirm} disabled={selectedIds.size === 0}> | |
| {mode === 'export' ? 'Export' : 'Import'} ({selectedIds.size}) | |
| </Button> | |
| </div> | |
| </div> | |