Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Malayalam
whisper
malayalam
indic-asr
fine-tuned
Instructions to use adalat-ai/whisper-medium-ml-rmft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adalat-ai/whisper-medium-ml-rmft with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="adalat-ai/whisper-medium-ml-rmft")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("adalat-ai/whisper-medium-ml-rmft") model = AutoModelForSpeechSeq2Seq.from_pretrained("adalat-ai/whisper-medium-ml-rmft") - Notebooks
- Google Colab
- Kaggle
Add library_name and pipeline_tag metadata
#1
by nielsr HF Staff - opened
Hi! I'm Niels from the Hugging Face community science team. This PR aims to improve the discoverability and usability of this model on the Hub.
The following changes were made:
- Added
library_name: transformersto the YAML metadata to enable the "Use in Transformers" button and automated code snippets. - Added
pipeline_tag: automatic-speech-recognitionto ensure the model appears in the correct category on the Hub. - Added an explicit link to the associated research paper in the model description.
- Preserved existing usage examples and benchmark data.
These updates help researchers and developers find and integrate your work more easily!
kavyamanohar changed pull request status to merged