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: 3,419 Bytes
8efb28e | 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 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 | <script lang="ts">
import { untrack } from 'svelte';
import { PROCESSING_INFO_TIMEOUT } from '$lib/constants';
import { useProcessingState } from '$lib/hooks/use-processing-state.svelte';
import { chatStore, isLoading, isChatStreaming } from '$lib/stores/chat.svelte';
import { activeMessages, activeConversation } from '$lib/stores/conversations.svelte';
import { config } from '$lib/stores/settings.svelte';
const processingState = useProcessingState();
let isCurrentConversationLoading = $derived(isLoading());
let isStreaming = $derived(isChatStreaming());
let processingDetails = $derived(processingState.getTechnicalDetails());
let processingVisible = $derived(processingDetails.length > 0);
let { onVisibilityChange }: { onVisibilityChange?: (visible: boolean) => void } = $props();
$effect(() => {
onVisibilityChange?.(processingVisible);
});
$effect(() => {
const conversation = activeConversation();
untrack(() => chatStore.setActiveProcessingConversation(conversation?.id ?? null));
});
$effect(() => {
const keepStatsVisible = config().keepStatsVisible;
const shouldMonitor = keepStatsVisible || isCurrentConversationLoading || isStreaming;
if (shouldMonitor) {
processingState.startMonitoring();
}
if (!isCurrentConversationLoading && !isStreaming && !keepStatsVisible) {
const timeout = setTimeout(() => {
if (!config().keepStatsVisible && !isChatStreaming()) {
processingState.stopMonitoring();
}
}, PROCESSING_INFO_TIMEOUT);
return () => clearTimeout(timeout);
}
});
$effect(() => {
const conversation = activeConversation();
const messages = activeMessages() as DatabaseMessage[];
const keepStatsVisible = config().keepStatsVisible;
if (keepStatsVisible && conversation) {
if (messages.length === 0) {
untrack(() => chatStore.clearProcessingState(conversation.id));
return;
}
if (!isCurrentConversationLoading && !isStreaming) {
untrack(() => chatStore.restoreProcessingStateFromMessages(messages, conversation.id));
}
}
});
</script>
<div
class={[
'chat-processing-info-container pointer-events-none relative w-full hidden md:block',
processingVisible && 'visible'
]}
>
<div class="chat-processing-info-content absolute bottom-4 left-1/2 -translate-x-1/2">
{#each processingDetails as detail (detail)}
<span class="chat-processing-info-detail pointer-events-auto backdrop-blur-sm">{detail}</span>
{/each}
</div>
</div>
<style>
.chat-processing-info-container {
position: sticky;
top: 0;
z-index: 10;
padding: 0 1rem 0.75rem;
opacity: 0;
transform: translateY(50%);
transition:
opacity 300ms ease-out,
transform 300ms ease-out;
}
.chat-processing-info-container.visible {
opacity: 1;
transform: translateY(0);
}
.chat-processing-info-content {
display: flex;
flex-wrap: wrap;
align-items: center;
gap: 1rem;
justify-content: center;
max-width: 48rem;
margin: 0 auto;
}
.chat-processing-info-detail {
color: var(--muted-foreground);
font-size: 0.75rem;
padding: 0.25rem 0.75rem;
border-radius: 0.375rem;
font-family:
ui-monospace, SFMono-Regular, 'SF Mono', Consolas, 'Liberation Mono', Menlo, monospace;
white-space: nowrap;
}
@media (max-width: 768px) {
.chat-processing-info-content {
gap: 0.5rem;
}
.chat-processing-info-detail {
font-size: 0.7rem;
padding: 0.2rem 0.5rem;
}
}
</style>
|