Instructions to use crcb/isear_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use crcb/isear_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="crcb/isear_bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("crcb/isear_bert") model = AutoModelForSequenceClassification.from_pretrained("crcb/isear_bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 118d848141668bd2a5a402bb628696abef32d6876675076a904aecf241cf6bc5
- Size of remote file:
- 499 MB
- SHA256:
- d7276812d3c5dbf3c2a0ad0a6f210d00490fe2980f430245e28c70a82f52932b
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