tipi/kyutai
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Config tweaks.

Browse Source
This commit is contained in:
laurent 2025-06-17 11:59:33 +02:00
parent a786ad8a0b
commit f87b8f1e6f
3 changed files with 11 additions and 11 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

10
README.md
View File

@ -7,7 +7,7 @@ Delayed Streams Modeling (DSM) is a flexible formulation for streaming, multimod
The main model handles english only, it has ~2.6B parameters.
#### PyTorch implementation
[[Hugging Face]](https://huggingface.co/kyutai/stt-2.6B-en)
[[Hugging Face]](https://huggingface.co/kyutai/stt-2.6b-en)
```bash
# wget https://github.com/metavoiceio/metavoice-src/raw/main/assets/bria.mp3
@ -15,15 +15,15 @@ python -m moshi.run_inference --hf-repo kyutai/stt-2.6B-en bria.mp3
```
#### MLX implementation
[[Hugging Face]](https://huggingface.co/kyutai/stt-2.6B-en-mlx)
[[Hugging Face]](https://huggingface.co/kyutai/stt-2.6b-en-mlx)
```bash
# wget https://github.com/metavoiceio/metavoice-src/raw/main/assets/bria.mp3
python -m moshi_mlx.run_inference --hf-repo kyutai/stt-2.6B-en-mlx bria.mp3 --temp 0
python -m moshi_mlx.run_inference --hf-repo kyutai/stt-2.6b-en-mlx bria.mp3 --temp 0
```
#### Rust implementation
[[Hugging Face]](https://huggingface.co/kyutai/stt-2.6B-en-candle)
[[Hugging Face]](https://huggingface.co/kyutai/stt-2.6b-en-candle)
The Rust implementation provides a server that can process multiple streaming
queries in parallel. Dependening on the amount of memory on your GPU, you may
@ -59,7 +59,7 @@ the data as fast as possible.
This model has ~1B parameters and supports both English and French.
#### Rust implementation
[[Hugging Face]](https://huggingface.co/kyutai/stt-1B-en_fr-candle)
[[Hugging Face]](https://huggingface.co/kyutai/stt-1b-en_fr-candle)
The only difference with the en only model is the config file used when
launching the server.

6
configs/config-stt-enfr-hf.toml
View File

@ -6,9 +6,9 @@ authorized_ids = ["open_token"]
[modules.asr]
path = "/api/asr-streaming"
type = "BatchedAsr"
lm_model_file = "hf://kyutai/stt-1B-en_fr-candle/model.safetensors"
text_tokenizer_file = "hf://kyutai/stt-1B-en_fr-candle/tokenizer_en_fr_audio_8000.model"
audio_tokenizer_file = "hf://kyutai/stt-1B-en_fr-candle/mimi-pytorch-e351c8d8@125.safetensors"
lm_model_file = "hf://kyutai/stt-1b-en_fr-candle/model.safetensors"
text_tokenizer_file = "hf://kyutai/stt-1b-en_fr-candle/tokenizer_en_fr_audio_8000.model"
audio_tokenizer_file = "hf://kyutai/stt-1b-en_fr-candle/mimi-pytorch-e351c8d8@125.safetensors"
asr_delay_in_tokens = 6
batch_size = 64
conditioning_learnt_padding = true

6
configs/config-stt-hf.toml
View File

@ -6,9 +6,9 @@ authorized_ids = ["open_token"]
[modules.asr]
path = "/api/asr-streaming"
type = "BatchedAsr"
lm_model_file = "hf://kyutai/stt-2.6B-en-candle/model.safetensors"
text_tokenizer_file = "hf://kyutai/stt-2.6B-en-candle/tokenizer_en_audio_4000.model"
audio_tokenizer_file = "hf://kyutai/stt-2.6B-en-candle/mimi-pytorch-e351c8d8@125.safetensors"
lm_model_file = "hf://kyutai/stt-2.6b-en-candle/model.safetensors"
text_tokenizer_file = "hf://kyutai/stt-2.6b-en-candle/tokenizer_en_audio_4000.model"
audio_tokenizer_file = "hf://kyutai/stt-2.6b-en-candle/mimi-pytorch-e351c8d8@125.safetensors"
asr_delay_in_tokens = 6
batch_size = 16
conditioning_learnt_padding = true