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
TdAI / llama.cpp /tools /ui /src /lib /components /app /navigation /SidebarNavigation /SidebarNavigationSearchResults.svelte
| <script lang="ts"> | |
| import { buildConversationTree } from '$lib/stores/conversations.svelte'; | |
| import SidebarNavigationConversationItem from './SidebarNavigationConversationItem.svelte'; | |
| interface Props { | |
| class?: string; | |
| searchQuery: string; | |
| filteredConversations: DatabaseConversation[]; | |
| currentChatId: string | undefined; | |
| onSelect: (id: string) => void; | |
| onEdit: (id: string) => void; | |
| onDelete: (id: string) => void; | |
| onStop: (id: string) => void; | |
| } | |
| let { | |
| class: className = '', | |
| searchQuery, | |
| filteredConversations, | |
| currentChatId, | |
| onSelect, | |
| onEdit, | |
| onDelete, | |
| onStop | |
| }: Props = $props(); | |
| let tree = $derived(buildConversationTree(filteredConversations)); | |
| const hasQuery = $derived(searchQuery.trim().length > 0); | |
| const showHeader = $derived(hasQuery && filteredConversations.length > 0); | |
| const emptyMessage = $derived(hasQuery ? 'No results found' : 'Start typing to see results'); | |
| </script> | |
| <div class="flex min-h-0 flex-1 flex-col gap-2 whitespace-nowrap {className}"> | |
| {#if showHeader} | |
| <div | |
| class="text-muted-foreground flex h-8 shrink-0 items-center rounded-md px-2 text-xs font-medium" | |
| > | |
| Search results | |
| </div> | |
| {/if} | |
| <div class="min-h-0 flex-1 overflow-y-auto"> | |
| <ul class="flex w-full min-w-0 flex-col gap-1"> | |
| {#each tree as { conversation, depth } (conversation.id)} | |
| <li class="group/item relative mb-1 p-0"> | |
| <SidebarNavigationConversationItem | |
| conversation={{ | |
| id: conversation.id, | |
| name: conversation.name, | |
| lastModified: conversation.lastModified, | |
| currNode: conversation.currNode, | |
| forkedFromConversationId: conversation.forkedFromConversationId, | |
| pinned: conversation.pinned | |
| }} | |
| {depth} | |
| isActive={currentChatId === conversation.id} | |
| {onSelect} | |
| {onEdit} | |
| {onDelete} | |
| {onStop} | |
| /> | |
| </li> | |
| {/each} | |
| {#if tree.length === 0} | |
| <li class="px-2 py-4 text-center"> | |
| <p class="mb-4 p-4 text-sm text-muted-foreground"> | |
| {emptyMessage} | |
| </p> | |
| </li> | |
| {/if} | |
| </ul> | |
| </div> | |
| </div> | |