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")# pip install -U transformers accelerate # 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
Download training_args.bin from caeher/mbert-sv: direct link, hf CLI and curl.
- Browser
- Download file 5.2 kB
-
https://huggingface.co/caeher/mbert-sv/resolve/main/training_args.bin
- Command line
-
hf download hf://caeher/mbert-sv/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/caeher/mbert-sv/resolve/main/training_args.bin
5.2 kB
- Xet hash:
- 252d073c8abb86c31420a1815195de7b8fa77ea94ad27660b3716225e45cb56e
- Size of remote file:
- 5.2 kB
- SHA256:
- 664f62a7a6b0edc9227d0ca0ae5e89648723af8722fa4d76cb3cc6282ff509c3
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