🤖 feature-extraction

w2v-bert-2.0

facebook/w2v-bert-2.0

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transformers
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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
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🚀 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.
👋 Need help with code?