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.
- 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
File size: 2,525 Bytes
15c3607 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 | <script lang="ts">
import * as AlertDialog from '$lib/components/ui/alert-dialog';
import { AlertTriangle, ArrowRight } from '@lucide/svelte';
import { goto } from '$app/navigation';
import { page } from '$app/state';
interface Props {
open: boolean;
modelName: string;
availableModels?: string[];
onOpenChange?: (open: boolean) => void;
}
let { open = $bindable(), modelName, availableModels = [], onOpenChange }: Props = $props();
function handleOpenChange(newOpen: boolean) {
open = newOpen;
onOpenChange?.(newOpen);
}
function handleSelectModel(model: string) {
// Build URL with selected model, preserving other params
const url = new URL(page.url);
url.searchParams.set('model', model);
handleOpenChange(false);
goto(url.toString());
}
</script>
<AlertDialog.Root {open} onOpenChange={handleOpenChange}>
<AlertDialog.Content class="max-w-lg">
<AlertDialog.Header>
<AlertDialog.Title class="flex items-center gap-2">
<AlertTriangle class="h-5 w-5 text-amber-500" />
Model Not Available
</AlertDialog.Title>
<AlertDialog.Description>
The requested model could not be found. Select an available model to continue.
</AlertDialog.Description>
</AlertDialog.Header>
<div class="space-y-3">
<div class="rounded-lg border border-amber-500/40 bg-amber-500/10 px-4 py-3 text-sm">
<p class="font-medium text-amber-600 dark:text-amber-400">
Requested: <code class="rounded bg-amber-500/20 px-1.5 py-0.5">{modelName}</code>
</p>
</div>
{#if availableModels.length > 0}
<div class="text-sm">
<p class="mb-2 font-medium text-muted-foreground">Select an available model:</p>
<div class="max-h-48 space-y-1 overflow-y-auto rounded-md border p-1">
{#each availableModels as model (model)}
<button
type="button"
class="group flex w-full items-center justify-between gap-2 rounded-sm px-3 py-2 text-left text-sm transition-colors hover:bg-accent hover:text-accent-foreground"
onclick={() => handleSelectModel(model)}
>
<span class="min-w-0 truncate font-mono text-xs">{model}</span>
<ArrowRight
class="h-4 w-4 shrink-0 text-muted-foreground opacity-0 transition-opacity group-hover:opacity-100"
/>
</button>
{/each}
</div>
</div>
{/if}
</div>
<AlertDialog.Footer>
<AlertDialog.Action onclick={() => handleOpenChange(false)}>Cancel</AlertDialog.Action>
</AlertDialog.Footer>
</AlertDialog.Content>
</AlertDialog.Root>
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