Instructions to use hypaai/Hypa-Whisper-Small-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use hypaai/Hypa-Whisper-Small-v2 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("automatic-speech-recognition", model="hypaai/Hypa-Whisper-Small-v2")

# Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq

processor = AutoProcessor.from_pretrained("hypaai/Hypa-Whisper-Small-v2")
model = AutoModelForSpeechSeq2Seq.from_pretrained("hypaai/Hypa-Whisper-Small-v2")

Notebooks
Google Colab
Kaggle
Local Apps Settings

Unsloth Studio

How to use hypaai/Hypa-Whisper-Small-v2 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 hypaai/Hypa-Whisper-Small-v2 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 hypaai/Hypa-Whisper-Small-v2 to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for hypaai/Hypa-Whisper-Small-v2 to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="hypaai/Hypa-Whisper-Small-v2",
    max_seq_length=2048,
)

Hypa-Whisper-Small-v2 / processor_config.json

Commit History

(Trained with Unsloth)

299f6ba
verified

hypaai commited on Jun 7

Commit History

(Trained with Unsloth) 299f6ba verified

(Trained with Unsloth)

299f6ba
verified