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, )
Upload model trained with Unsloth
Browse filesUpload model trained with Unsloth 2x faster
- processor_config.json +17 -0
- tokenizer.json +0 -0
- tokenizer_config.json +31 -0
processor_config.json
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{
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"feature_extractor": {
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"chunk_length": 30,
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"dither": 0.0,
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"feature_extractor_type": "WhisperFeatureExtractor",
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"feature_size": 80,
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"hop_length": 160,
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"n_fft": 400,
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"n_samples": 480000,
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"nb_max_frames": 3000,
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"padding_side": "left",
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"padding_value": 0.0,
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"return_attention_mask": false,
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"sampling_rate": 16000
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},
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"processor_class": "WhisperProcessor"
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}
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tokenizer.json
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tokenizer_config.json
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{
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"add_prefix_space": false,
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"backend": "tokenizers",
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"bos_token": "<|endoftext|>",
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"clean_up_tokenization_spaces": true,
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"eos_token": "<|endoftext|>",
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"errors": "replace",
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"extra_special_tokens": [
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"<|ann|>",
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"<|efi|>",
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"<|ego|>",
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"<|ibb|>",
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"<|idm|>",
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"<|igl|>",
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"<|ig|>",
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"<|nup|>",
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"<|tiv|>",
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"<|urh|>"
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],
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"is_local": false,
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"language": "english",
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"model_max_length": 1024,
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"pad_token": "<|endoftext|>",
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"padding_side": "left",
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"predict_timestamps": false,
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"processor_class": "WhisperProcessor",
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"return_attention_mask": false,
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"task": "translate",
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"tokenizer_class": "WhisperTokenizer",
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"unk_token": "<|endoftext|>"
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}
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