Automatic Speech Recognition
Transformers
Safetensors
Khmer
English
French
psarai_s2s
feature-extraction
speech-to-speech-translation
speech-translation
text-to-speech
khmer
code-switching
custom_code
Instructions to use nphearum/PsarAI-S2S with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nphearum/PsarAI-S2S with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="nphearum/PsarAI-S2S", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nphearum/PsarAI-S2S", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download mt/tokenizer.json from nphearum/PsarAI-S2S: direct link, hf CLI and curl.
- Browser
- Download file 32.2 MB
-
https://huggingface.co/nphearum/PsarAI-S2S/resolve/main/mt/tokenizer.json
- Command line
-
hf download hf://nphearum/PsarAI-S2S/mt/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/nphearum/PsarAI-S2S/resolve/main/mt/tokenizer.json
32.2 MB
- Xet hash:
- 45220759fb3b9ef9472748457e62d743c2294f5647f8d177c2f1c70bdb510049
- Size of remote file:
- 32.2 MB
- SHA256:
- 6a84f5760bddb5db107810ae92bd04e4368e2fec19f256ece0082bba04c0b864
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