Text Classification
Transformers
Safetensors
Spanish
bert
hate-speech
toxicity
spanish
el-salvador
mbert
Eval Results (legacy)
text-embeddings-inference
Instructions to use caeher/mbert-sv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use caeher/mbert-sv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="caeher/mbert-sv")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("caeher/mbert-sv") model = AutoModelForSequenceClassification.from_pretrained("caeher/mbert-sv", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d9a60bc08bb644b1de07e939a4aaf4e333e9f6854c478e12511a7f1b3a4c986d
- Size of remote file:
- 5.2 kB
- SHA256:
- be351f95ce0b99bab71f3fe9f100d435804bd29fc6ce4f857bce35a9a1603d7c
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