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
File size: 7,522 Bytes
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/**
* AudioRecorder - Browser-based audio recording with MediaRecorder API
*
* This class provides a complete audio recording solution using the browser's MediaRecorder API.
* It handles microphone access, recording state management, and audio format optimization.
*
* **Features:**
* - Automatic microphone permission handling
* - Audio enhancement (echo cancellation, noise suppression, auto gain)
* - Multiple format support with fallback (WAV, WebM, MP4, AAC)
* - Real-time recording state tracking
* - Proper cleanup and resource management
*/
export class AudioRecorder {
private mediaRecorder: MediaRecorder | null = null;
private audioChunks: Blob[] = [];
private stream: MediaStream | null = null;
private recordingState: boolean = false;
async startRecording(): Promise<void> {
try {
this.stream = await navigator.mediaDevices.getUserMedia({
audio: {
echoCancellation: true,
noiseSuppression: true,
autoGainControl: true
}
});
this.initializeRecorder(this.stream);
this.audioChunks = [];
// Start recording with a small timeslice to ensure we get data
this.mediaRecorder!.start(100);
this.recordingState = true;
} catch (error) {
console.error('Failed to start recording:', error);
throw new Error('Failed to access microphone. Please check permissions.');
}
}
async stopRecording(): Promise<Blob> {
return new Promise((resolve, reject) => {
const recorder = this.mediaRecorder;
const chunks = this.audioChunks;
const stream = this.stream;
if (!recorder || recorder.state === 'inactive') {
reject(new Error('No active recording to stop'));
return;
}
// Detach instance state right away so a new startRecording can take over without race
this.mediaRecorder = null;
this.audioChunks = [];
this.stream = null;
this.recordingState = false;
recorder.onstop = () => {
const audioBlob = new Blob(chunks, {
type: recorder.mimeType || MimeTypeAudio.WAV
});
if (stream) {
for (const track of stream.getTracks()) {
track.stop();
}
}
resolve(audioBlob);
};
recorder.onerror = (event) => {
console.error('Recording error:', event);
if (stream) {
for (const track of stream.getTracks()) {
track.stop();
}
}
reject(new Error('Recording failed'));
};
recorder.stop();
});
}
isRecording(): boolean {
return this.recordingState;
}
cancelRecording(): void {
const recorder = this.mediaRecorder;
const stream = this.stream;
this.mediaRecorder = null;
this.audioChunks = [];
this.stream = null;
this.recordingState = false;
if (recorder && recorder.state !== 'inactive') {
// Drop the original handlers so the pending stop event does not touch the instance
recorder.onstop = null;
recorder.onerror = null;
recorder.stop();
}
if (stream) {
for (const track of stream.getTracks()) {
track.stop();
}
}
}
private initializeRecorder(stream: MediaStream): void {
const options: MediaRecorderOptions = {};
if (MediaRecorder.isTypeSupported(MimeTypeAudio.WAV)) {
options.mimeType = MimeTypeAudio.WAV;
} else if (MediaRecorder.isTypeSupported(MimeTypeAudio.WEBM_OPUS)) {
options.mimeType = MimeTypeAudio.WEBM_OPUS;
} else if (MediaRecorder.isTypeSupported(MimeTypeAudio.WEBM)) {
options.mimeType = MimeTypeAudio.WEBM;
} else if (MediaRecorder.isTypeSupported(MimeTypeAudio.MP4)) {
options.mimeType = MimeTypeAudio.MP4;
} else {
console.warn('No preferred audio format supported, using default');
}
this.mediaRecorder = new MediaRecorder(stream, options);
this.mediaRecorder.ondataavailable = (event) => {
if (event.data.size > 0) {
this.audioChunks.push(event.data);
}
};
this.mediaRecorder.onstop = () => {
this.recordingState = false;
};
this.mediaRecorder.onerror = (event) => {
console.error('MediaRecorder error:', event);
this.recordingState = false;
};
}
}
export async function convertToWav(audioBlob: Blob): Promise<Blob> {
try {
if (audioBlob.type.includes('wav')) {
return audioBlob;
}
const arrayBuffer = await audioBlob.arrayBuffer();
// eslint-disable-next-line @typescript-eslint/no-explicit-any
const audioContext = new (window.AudioContext || (window as any).webkitAudioContext)();
try {
const audioBuffer = await audioContext.decodeAudioData(arrayBuffer);
return audioBufferToWav(audioBuffer);
} finally {
audioContext.close();
}
} catch (error) {
console.error('Failed to convert audio to WAV:', error);
return audioBlob;
}
}
function audioBufferToWav(buffer: AudioBuffer): Blob {
const length = buffer.length;
const numberOfChannels = buffer.numberOfChannels;
const sampleRate = buffer.sampleRate;
const bytesPerSample = 2; // 16-bit
const blockAlign = numberOfChannels * bytesPerSample;
const byteRate = sampleRate * blockAlign;
const dataSize = length * blockAlign;
const bufferSize = 44 + dataSize;
const arrayBuffer = new ArrayBuffer(bufferSize);
const view = new DataView(arrayBuffer);
const writeString = (offset: number, string: string) => {
for (let i = 0; i < string.length; i++) {
view.setUint8(offset + i, string.charCodeAt(i));
}
};
writeString(0, 'RIFF'); // ChunkID
view.setUint32(4, bufferSize - 8, true); // ChunkSize
writeString(8, 'WAVE'); // Format
writeString(12, 'fmt '); // Subchunk1ID
view.setUint32(16, 16, true); // Subchunk1Size
view.setUint16(20, 1, true); // AudioFormat (PCM)
view.setUint16(22, numberOfChannels, true); // NumChannels
view.setUint32(24, sampleRate, true); // SampleRate
view.setUint32(28, byteRate, true); // ByteRate
view.setUint16(32, blockAlign, true); // BlockAlign
view.setUint16(34, 16, true); // BitsPerSample
writeString(36, 'data'); // Subchunk2ID
view.setUint32(40, dataSize, true); // Subchunk2Size
// Cache channel arrays, write PCM via Int16Array (native little-endian, matches WAV)
const channels: Float32Array[] = new Array(numberOfChannels);
for (let c = 0; c < numberOfChannels; c++) {
channels[c] = buffer.getChannelData(c);
}
const pcm = new Int16Array(arrayBuffer, 44, length * numberOfChannels);
let p = 0;
for (let i = 0; i < length; i++) {
for (let c = 0; c < numberOfChannels; c++) {
let s = channels[c][i];
if (s > 1) s = 1;
else if (s < -1) s = -1;
pcm[p++] = s * 0x7fff;
}
}
return new Blob([arrayBuffer], { type: MimeTypeAudio.WAV });
}
/**
* Create a File object from audio blob with timestamp-based naming
* @param audioBlob - The audio blob to wrap
* @param filename - Optional custom filename
* @returns File object with appropriate name and metadata
*/
export function createAudioFile(audioBlob: Blob, filename?: string): File {
const timestamp = new Date().toISOString().replace(/[:.]/g, '-');
const extension = audioBlob.type.includes('wav') ? 'wav' : 'mp3';
const defaultFilename = `recording-${timestamp}.${extension}`;
return new File([audioBlob], filename || defaultFilename, {
type: audioBlob.type,
lastModified: Date.now()
});
}
/**
* Check if audio recording is supported in the current browser
* @returns True if MediaRecorder and getUserMedia are available
*/
export function isAudioRecordingSupported(): boolean {
return !!(
typeof navigator !== 'undefined' &&
navigator.mediaDevices &&
typeof navigator.mediaDevices.getUserMedia === 'function' &&
typeof window !== 'undefined' &&
window.MediaRecorder
);
}
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