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 /mcp /McpServerCard /McpServerCardHeader.svelte
| <script lang="ts"> | |
| import { Switch } from '$lib/components/ui/switch'; | |
| import { Badge } from '$lib/components/ui/badge'; | |
| import { McpCapabilitiesBadges, McpServerIdentity } from '$lib/components/app/mcp'; | |
| import { MCP_TRANSPORT_LABELS, MCP_TRANSPORT_ICONS } from '$lib/constants'; | |
| import { MCPTransportType } from '$lib/enums'; | |
| import type { MCPServerInfo, MCPCapabilitiesInfo } from '$lib/types'; | |
| interface Props { | |
| displayName: string; | |
| faviconUrl?: string | null; | |
| enabled: boolean; | |
| disabled?: boolean; | |
| onToggle: (enabled: boolean) => void; | |
| serverInfo?: MCPServerInfo; | |
| capabilities?: MCPCapabilitiesInfo; | |
| transportType?: MCPTransportType; | |
| } | |
| let { | |
| displayName, | |
| faviconUrl, | |
| enabled, | |
| disabled = false, | |
| onToggle, | |
| serverInfo, | |
| capabilities, | |
| transportType | |
| }: Props = $props(); | |
| </script> | |
| <div class="space-y-3"> | |
| <div class="flex items-start justify-between gap-3"> | |
| <div class="flex min-w-0 flex-col gap-3"> | |
| <div class="inline-flex items-center gap-2"> | |
| <McpServerIdentity | |
| {displayName} | |
| {faviconUrl} | |
| {serverInfo} | |
| iconClass="h-5 w-5" | |
| iconRounded="rounded" | |
| nameClass="leading-6 font-medium" | |
| /> | |
| </div> | |
| {#if capabilities || transportType} | |
| <div class="flex flex-wrap items-center gap-1.5"> | |
| {#if transportType} | |
| {@const TransportIcon = MCP_TRANSPORT_ICONS[transportType]} | |
| <Badge variant="outline" class="h-5 gap-1 px-1.5 text-[10px]"> | |
| {#if TransportIcon} | |
| <TransportIcon class="h-3 w-3" /> | |
| {/if} | |
| {MCP_TRANSPORT_LABELS[transportType] || transportType} | |
| </Badge> | |
| {/if} | |
| {#if capabilities} | |
| <McpCapabilitiesBadges {capabilities} /> | |
| {/if} | |
| </div> | |
| {/if} | |
| </div> | |
| <div class="flex shrink-0 items-center pl-2"> | |
| <Switch checked={enabled} {disabled} onCheckedChange={onToggle} /> | |
| </div> | |
| </div> | |
| </div> | |