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 * as AlertDialog from '$lib/components/ui/alert-dialog'; | |
| import { AlertTriangle, TimerOff } from '@lucide/svelte'; | |
| import { ErrorDialogType } from '$lib/enums'; | |
| interface Props { | |
| open: boolean; | |
| type: ErrorDialogType; | |
| message: string; | |
| contextInfo?: { n_prompt_tokens: number; n_ctx: number }; | |
| onOpenChange?: (open: boolean) => void; | |
| } | |
| let { open = $bindable(), type, message, contextInfo, onOpenChange }: Props = $props(); | |
| const isTimeout = $derived(type === ErrorDialogType.TIMEOUT); | |
| const title = $derived(isTimeout ? 'TCP Timeout' : 'Server Error'); | |
| const description = $derived( | |
| isTimeout | |
| ? 'The request did not receive a response from the server before timing out.' | |
| : 'The server responded with an error message. Review the details below.' | |
| ); | |
| const iconClass = $derived(isTimeout ? 'text-destructive' : 'text-amber-500'); | |
| const badgeClass = $derived( | |
| isTimeout | |
| ? 'border-destructive/40 bg-destructive/10 text-destructive' | |
| : 'border-amber-500/40 bg-amber-500/10 text-amber-600 dark:text-amber-400' | |
| ); | |
| function handleOpenChange(newOpen: boolean) { | |
| open = newOpen; | |
| onOpenChange?.(newOpen); | |
| } | |
| </script> | |
| <AlertDialog.Root {open} onOpenChange={handleOpenChange}> | |
| <AlertDialog.Content> | |
| <AlertDialog.Header> | |
| <AlertDialog.Title class="flex items-center gap-2"> | |
| {#if isTimeout} | |
| <TimerOff class={`h-5 w-5 ${iconClass}`} /> | |
| {:else} | |
| <AlertTriangle class={`h-5 w-5 ${iconClass}`} /> | |
| {/if} | |
| {title} | |
| </AlertDialog.Title> | |
| <AlertDialog.Description> | |
| {description} | |
| </AlertDialog.Description> | |
| </AlertDialog.Header> | |
| <div class={`rounded-lg border px-4 py-3 text-sm ${badgeClass}`}> | |
| <p class="font-medium">{message}</p> | |
| {#if contextInfo} | |
| <div class="mt-2 space-y-1 text-xs opacity-80"> | |
| <p> | |
| <span class="font-medium">Prompt tokens:</span> | |
| {contextInfo.n_prompt_tokens.toLocaleString()} | |
| </p> | |
| {#if contextInfo.n_ctx} | |
| <p> | |
| <span class="font-medium">Context size:</span> | |
| {contextInfo.n_ctx.toLocaleString()} | |
| </p> | |
| {/if} | |
| </div> | |
| {/if} | |
| </div> | |
| <AlertDialog.Footer> | |
| <AlertDialog.Action onclick={() => handleOpenChange(false)}>Close</AlertDialog.Action> | |
| </AlertDialog.Footer> | |
| </AlertDialog.Content> | |
| </AlertDialog.Root> | |