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
- 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
- Atomic Chat
File size: 3,555 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 | import { describe, expect, it } from 'vitest';
import { ChatService } from '$lib/services/chat.service';
import type { ApiStreamSession } from '$lib/types';
function makeSession(overrides: Partial<ApiStreamSession>): ApiStreamSession {
return {
conversation_id: 'conv',
is_done: true,
total_bytes: 0,
started_at: 0,
completed_at: 0,
...overrides
};
}
describe('selectActiveStream', () => {
it('returns null on empty input', () => {
expect(ChatService.selectActiveStream([])).toBeNull();
});
it('returns null on null or undefined input', () => {
expect(ChatService.selectActiveStream(null)).toBeNull();
expect(ChatService.selectActiveStream(undefined)).toBeNull();
});
it('returns the single session when it is running', () => {
const s = makeSession({ conversation_id: 'only', is_done: false, started_at: 42 });
expect(ChatService.selectActiveStream([s])).toBe(s);
});
it('returns null when the single session is finalized', () => {
const s = makeSession({ conversation_id: 'only', is_done: true, started_at: 42 });
expect(ChatService.selectActiveStream([s])).toBeNull();
});
it('prefers a still running session over a finalized one regardless of started_at', () => {
const finalized = makeSession({ conversation_id: 'old', is_done: true, started_at: 1000 });
const running = makeSession({ conversation_id: 'new', is_done: false, started_at: 10 });
expect(ChatService.selectActiveStream([finalized, running])?.conversation_id).toBe('new');
expect(ChatService.selectActiveStream([running, finalized])?.conversation_id).toBe('new');
});
it('among running sessions, picks the most recently started one', () => {
const a = makeSession({ conversation_id: 'a', is_done: false, started_at: 100 });
const b = makeSession({ conversation_id: 'b', is_done: false, started_at: 200 });
const c = makeSession({ conversation_id: 'c', is_done: false, started_at: 150 });
expect(ChatService.selectActiveStream([a, b, c])?.conversation_id).toBe('b');
expect(ChatService.selectActiveStream([c, a, b])?.conversation_id).toBe('b');
});
it('returns null when all sessions are finalized, the DB already holds the content', () => {
const a = makeSession({ conversation_id: 'a', is_done: true, started_at: 10 });
const b = makeSession({ conversation_id: 'b', is_done: true, started_at: 30 });
const c = makeSession({ conversation_id: 'c', is_done: true, started_at: 20 });
expect(ChatService.selectActiveStream([a, b, c])).toBeNull();
});
it('keeps the first match on ties when both are running with identical started_at', () => {
// reduce visits left to right, the initial accumulator stays unless a strictly greater value appears
const a = makeSession({ conversation_id: 'first', is_done: false, started_at: 50 });
const b = makeSession({ conversation_id: 'second', is_done: false, started_at: 50 });
expect(ChatService.selectActiveStream([a, b])?.conversation_id).toBe('first');
});
it('handles a typical realistic mix: two finalized old, one freshly running, one freshly finalized', () => {
const old1 = makeSession({ conversation_id: 'old1', is_done: true, started_at: 100 });
const old2 = makeSession({ conversation_id: 'old2', is_done: true, started_at: 200 });
const freshFin = makeSession({ conversation_id: 'freshFin', is_done: true, started_at: 500 });
const running = makeSession({ conversation_id: 'running', is_done: false, started_at: 400 });
expect(ChatService.selectActiveStream([old1, old2, freshFin, running])?.conversation_id).toBe(
'running'
);
});
});
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