Instructions to use alecmontero/BLOOM-Meta4Types-ft-ES with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alecmontero/BLOOM-Meta4Types-ft-ES with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="alecmontero/BLOOM-Meta4Types-ft-ES")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("alecmontero/BLOOM-Meta4Types-ft-ES") model = AutoModelForSequenceClassification.from_pretrained("alecmontero/BLOOM-Meta4Types-ft-ES", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from alecmontero/BLOOM-Meta4Types-ft-ES: direct link, hf CLI and curl.
- Browser
- Download file 14.5 MB
-
https://huggingface.co/alecmontero/BLOOM-Meta4Types-ft-ES/resolve/main/tokenizer.json
- Command line
-
hf download hf://alecmontero/BLOOM-Meta4Types-ft-ES/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/alecmontero/BLOOM-Meta4Types-ft-ES/resolve/main/tokenizer.json
14.5 MB
- Xet hash:
- 12522da66e1204bbf90d278c3f4e6f42323a37f99880b139e684339124541ddd
- Size of remote file:
- 14.5 MB
- SHA256:
- ae95e8c782e419456cf0ae52d465317dca8c4535e4088405a5712eeda1b3670c
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