Automatic Speech Recognition
Transformers
Safetensors
English
whisper
text-generation-inference
unsloth
trl
Instructions to use Danieljava/Hypa-Whisper-small-2026-03-31-translate-check with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Danieljava/Hypa-Whisper-small-2026-03-31-translate-check with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Danieljava/Hypa-Whisper-small-2026-03-31-translate-check")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Danieljava/Hypa-Whisper-small-2026-03-31-translate-check") model = AutoModelForSpeechSeq2Seq.from_pretrained("Danieljava/Hypa-Whisper-small-2026-03-31-translate-check", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use Danieljava/Hypa-Whisper-small-2026-03-31-translate-check 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 Danieljava/Hypa-Whisper-small-2026-03-31-translate-check 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 Danieljava/Hypa-Whisper-small-2026-03-31-translate-check to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Danieljava/Hypa-Whisper-small-2026-03-31-translate-check to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="Danieljava/Hypa-Whisper-small-2026-03-31-translate-check", max_seq_length=2048, )
File size: 408 Bytes
a9b8b83 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | {
"feature_extractor": {
"chunk_length": 30,
"dither": 0.0,
"feature_extractor_type": "WhisperFeatureExtractor",
"feature_size": 80,
"hop_length": 160,
"n_fft": 400,
"n_samples": 480000,
"nb_max_frames": 3000,
"padding_side": "left",
"padding_value": 0.0,
"return_attention_mask": false,
"sampling_rate": 16000
},
"processor_class": "WhisperProcessor"
}
|