Instructions to use SaladSlayer00/Prov_SML with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SaladSlayer00/Prov_SML with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="SaladSlayer00/Prov_SML")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("SaladSlayer00/Prov_SML") model = AutoModelForSpeechSeq2Seq.from_pretrained("SaladSlayer00/Prov_SML", device_map="auto") - Notebooks
- Google Colab
- Kaggle
metadata
title: Prov SML
emoji: 😻
colorFrom: pink
colorTo: yellow
sdk: gradio
sdk_version: 4.7.1
app_file: app.py
pinned: false
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference