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: 8,181 Bytes
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import * as Dialog from '$lib/components/ui/dialog';
import * as Table from '$lib/components/ui/table';
import { BadgesModality, ActionIconCopyToClipboard } from '$lib/components/app';
import { serverStore } from '$lib/stores/server.svelte';
import { modelsStore, modelOptions, modelsLoading } from '$lib/stores/models.svelte';
import { formatFileSize, formatParameters, formatNumber } from '$lib/utils';
import type { ApiLlamaCppServerProps } from '$lib/types';
interface Props {
open?: boolean;
onOpenChange?: (open: boolean) => void;
// when set, fetch props from the child process (router mode)
modelId?: string | null;
}
let { open = $bindable(), onOpenChange, modelId = null }: Props = $props();
let isRouter = $derived(serverStore.isRouterMode);
// per-model props fetched from the child process
let routerModelProps = $state<ApiLlamaCppServerProps | null>(null);
let isLoadingRouterProps = $state(false);
// in router mode use per-model props, otherwise use global props
let serverProps = $derived(isRouter && modelId ? routerModelProps : serverStore.props);
let modelName = $derived(isRouter && modelId ? modelId : modelsStore.singleModelName);
let models = $derived(modelOptions());
let isLoadingModels = $derived(modelsLoading());
// in router mode, find the model option matching modelId
// in single mode, use the first model as before
let firstModel = $derived.by(() => {
if (isRouter && modelId) {
return models.find((m) => m.model === modelId) ?? null;
}
return models[0] ?? null;
});
// Get modalities from modelStore using the model ID from the first model
let modalities = $derived.by(() => {
if (!firstModel?.id) return [];
return modelsStore.getModelModalitiesArray(firstModel.id);
});
// Ensure models are fetched when dialog opens
$effect(() => {
if (open && models.length === 0) {
modelsStore.fetch();
}
});
// fetch per-model props from child process when dialog opens in router mode
$effect(() => {
if (open && isRouter && modelId) {
isLoadingRouterProps = true;
modelsStore
.fetchModelProps(modelId)
.then((props) => {
routerModelProps = props;
})
.catch(() => {
routerModelProps = null;
})
.finally(() => {
isLoadingRouterProps = false;
});
}
if (!open) {
routerModelProps = null;
}
});
</script>
<Dialog.Root bind:open {onOpenChange}>
<Dialog.Content class="@container z-9999 !max-h-[80dvh] !max-w-[60rem] max-w-full">
<style>
@container (max-width: 56rem) {
.resizable-text-container {
max-width: calc(100vw - var(--threshold));
}
}
</style>
<Dialog.Header>
<Dialog.Title>Model Information</Dialog.Title>
<Dialog.Description>Current model details and capabilities</Dialog.Description>
</Dialog.Header>
<div class="space-y-6 py-4">
{#if isLoadingModels || isLoadingRouterProps}
<div class="flex items-center justify-center py-8">
<div class="text-sm text-muted-foreground">Loading model information...</div>
</div>
{:else if firstModel}
{@const modelMeta = firstModel.meta}
{#if serverProps}
<Table.Root>
<Table.Header>
<Table.Row>
<Table.Head class="w-[10rem]">Model</Table.Head>
<Table.Head>
<div class="inline-flex items-center gap-2">
<span
class="resizable-text-container min-w-0 flex-1 truncate"
style:--threshold="12rem"
>
{modelName}
</span>
<ActionIconCopyToClipboard
text={modelName || ''}
canCopy={!!modelName}
ariaLabel="Copy model name to clipboard"
/>
</div>
</Table.Head>
</Table.Row>
</Table.Header>
<Table.Body>
<!-- Model Path -->
<Table.Row>
<Table.Cell class="h-10 align-middle font-medium">File Path</Table.Cell>
<Table.Cell
class="inline-flex h-10 items-center gap-2 align-middle font-mono text-xs"
>
<span
class="resizable-text-container min-w-0 flex-1 truncate"
style:--threshold="14rem"
>
{serverProps.model_path}
</span>
<ActionIconCopyToClipboard
text={serverProps.model_path}
ariaLabel="Copy model path to clipboard"
/>
</Table.Cell>
</Table.Row>
<!-- Context Size -->
{#if serverProps?.default_generation_settings?.n_ctx}
<Table.Row>
<Table.Cell class="h-10 align-middle font-medium">Context Size</Table.Cell>
<Table.Cell
>{formatNumber(serverProps.default_generation_settings.n_ctx)} tokens</Table.Cell
>
</Table.Row>
{:else}
<Table.Row>
<Table.Cell class="h-10 align-middle font-medium text-red-500"
>Context Size</Table.Cell
>
<Table.Cell class="text-red-500">Not available</Table.Cell>
</Table.Row>
{/if}
<!-- Training Context -->
{#if modelMeta?.n_ctx_train}
<Table.Row>
<Table.Cell class="h-10 align-middle font-medium">Training Context</Table.Cell>
<Table.Cell>{formatNumber(modelMeta.n_ctx_train)} tokens</Table.Cell>
</Table.Row>
{/if}
<!-- Model Size -->
{#if modelMeta?.size}
<Table.Row>
<Table.Cell class="h-10 align-middle font-medium">Model Size</Table.Cell>
<Table.Cell>{formatFileSize(modelMeta.size)}</Table.Cell>
</Table.Row>
{/if}
<!-- Parameters -->
{#if modelMeta?.n_params}
<Table.Row>
<Table.Cell class="h-10 align-middle font-medium">Parameters</Table.Cell>
<Table.Cell>{formatParameters(modelMeta.n_params)}</Table.Cell>
</Table.Row>
{/if}
<!-- Embedding Size -->
{#if modelMeta?.n_embd}
<Table.Row>
<Table.Cell class="align-middle font-medium">Embedding Size</Table.Cell>
<Table.Cell>{formatNumber(modelMeta.n_embd)}</Table.Cell>
</Table.Row>
{/if}
<!-- Vocabulary Size -->
{#if modelMeta?.n_vocab}
<Table.Row>
<Table.Cell class="align-middle font-medium">Vocabulary Size</Table.Cell>
<Table.Cell>{formatNumber(modelMeta.n_vocab)} tokens</Table.Cell>
</Table.Row>
{/if}
<!-- Vocabulary Type -->
{#if modelMeta?.vocab_type}
<Table.Row>
<Table.Cell class="align-middle font-medium">Vocabulary Type</Table.Cell>
<Table.Cell class="align-middle capitalize">{modelMeta.vocab_type}</Table.Cell>
</Table.Row>
{/if}
<!-- Total Slots -->
<Table.Row>
<Table.Cell class="align-middle font-medium">Parallel Slots</Table.Cell>
<Table.Cell>{serverProps.total_slots}</Table.Cell>
</Table.Row>
<!-- Modalities -->
{#if modalities.length > 0}
<Table.Row>
<Table.Cell class="align-middle font-medium">Modalities</Table.Cell>
<Table.Cell>
<div class="flex flex-wrap gap-1">
<BadgesModality {modalities} />
</div>
</Table.Cell>
</Table.Row>
{/if}
<!-- Build Info -->
<Table.Row>
<Table.Cell class="align-middle font-medium">Build Info</Table.Cell>
<Table.Cell class="align-middle font-mono text-xs"
>{serverProps.build_info}</Table.Cell
>
</Table.Row>
<!-- Chat Template -->
{#if serverProps.chat_template}
<Table.Row>
<Table.Cell class="align-middle font-medium">Chat Template</Table.Cell>
<Table.Cell class="py-10">
<div class="rounded-md bg-muted p-4">
<pre
class="font-mono text-xs whitespace-pre-wrap">{serverProps.chat_template}</pre>
</div>
</Table.Cell>
</Table.Row>
{/if}
</Table.Body>
</Table.Root>
{/if}
{:else if !isLoadingModels}
<div class="flex items-center justify-center py-8">
<div class="text-sm text-muted-foreground">No model information available</div>
</div>
{/if}
</div>
</Dialog.Content>
</Dialog.Root>
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