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How to use BricksDisplay/chatterbox-multilingual-ONNX-q4 with Transformers.js:
// npm i @huggingface/transformers
import { pipeline } from '@huggingface/transformers';
// Allocate pipeline
const pipe = await pipeline('text-to-speech', 'BricksDisplay/chatterbox-multilingual-ONNX-q4');Q4 weight-only quantized version of onnx-community/chatterbox-multilingual-ONNX for use with Transformers.js and ONNX Runtime Web.
| Model | Original (FP32) | Q4 Quantized |
|---|---|---|
| speech_encoder.onnx | 564 MB | 172 MB |
| embed_tokens.onnx | 66 MB | 65 MB |
| language_model.onnx | 2.0 GB | 338 MB |
| conditional_decoder.onnx | 510 MB | 215 MB |
| Total | 3.2 GB | 790 MB |
import onnxruntime
# Load Q4 models - single files, no external data needed
speech_encoder = onnxruntime.InferenceSession("onnx/speech_encoder.onnx")
embed_tokens = onnxruntime.InferenceSession("onnx/embed_tokens.onnx")
language_model = onnxruntime.InferenceSession("onnx/language_model.onnx")
conditional_decoder = onnxruntime.InferenceSession("onnx/conditional_decoder.onnx")
// Models are single-file ONNX format, compatible with ONNX Runtime Web
import { AutoTokenizer } from '@huggingface/transformers';
const tokenizer = await AutoTokenizer.from_pretrained('ipsilondev/chatterbox-multilingual-ONNX-q4');
MatMulNBitsQuantizerWhen using these models, ensure you use the correct parameters:
repetition_penalty = 1.2 # CRITICAL: Do NOT use 2.0 - causes infinite loops
temperature = 0.8
top_p = 0.95
min_p = 0.05
| Code | Language | Code | Language |
|---|---|---|---|
| ar | Arabic | ko | Korean |
| da | Danish | ms | Malay |
| de | German | nl | Dutch |
| el | Greek | no | Norwegian |
| en | English | pl | Polish |
| es | Spanish | pt | Portuguese |
| fi | Finnish | ru | Russian |
| fr | French | sv | Swedish |
| he | Hebrew | sw | Swahili |
| hi | Hindi | tr | Turkish |
| it | Italian | zh | Chinese |
| ja | Japanese |
MIT License (same as original model)
Base model
ResembleAI/chatterbox