Instructions to use Ojeda01/bert_base_cased_MultiClass_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ojeda01/bert_base_cased_MultiClass_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ojeda01/bert_base_cased_MultiClass_v2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ojeda01/bert_base_cased_MultiClass_v2") model = AutoModelForSequenceClassification.from_pretrained("Ojeda01/bert_base_cased_MultiClass_v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
e832f98 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:2e5efad16e633df284ee6b0f04acd3b6f07b17b8acdf271a48688b0566b5057b
size 3579
|