Model Details
Full Model IDfacebook/w2v-bert-2.0
Pipeline / Taskfeature-extraction
Librarytransformers
Downloads (all-time)3.2M
Likes213
Last Modified1/25/2024
Author / Orgfacebook
PrivateNo — public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("feature-extraction", model="facebook/w2v-bert-2.0")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerssafetensorswav2vec2-bertfeature-extractionafamarasazbebnbsbgcacszhcydadeelenetfifroromgaglguha
More feature-extraction Models
See all →🚀 Use This Model
Access model files, inference API, and full documentation on Hugging Face.
Open on Hugging Face →Browse Model Files ↗← Browse All Models🤖 Task: feature-extraction
This model is designed for the feature-extraction task. Explore more models for this use case.
All feature-extraction Models →📊 Popularity
⬇ Downloads3.2M
❤️ Community Likes213
🛠️ Requirements
- →Install: pip install transformers
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.