Instructions to use barca-boy/sent_analysis_bert_simple with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use barca-boy/sent_analysis_bert_simple with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="barca-boy/sent_analysis_bert_simple")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("barca-boy/sent_analysis_bert_simple") model = AutoModelForSequenceClassification.from_pretrained("barca-boy/sent_analysis_bert_simple", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 084181617a8ef494dba8f05161d64233c661c6522c41de4b1a1e572846a683d8
- Size of remote file:
- 5.18 kB
- SHA256:
- a46f4281b83933e7f36d0253262e2330c512818d62f81de7a457d3eab3515ab5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.