Instructions to use Mike-plotpointe/Comments-Classifier-Bert-Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mike-plotpointe/Comments-Classifier-Bert-Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Mike-plotpointe/Comments-Classifier-Bert-Model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Mike-plotpointe/Comments-Classifier-Bert-Model") model = AutoModelForSequenceClassification.from_pretrained("Mike-plotpointe/Comments-Classifier-Bert-Model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3fbff4491e9dbc143ee310b16e8eb2861e8c763407803d7ff27eac03a51914d3
- Size of remote file:
- 1.34 GB
- SHA256:
- 3faa8de327acec7a1fd88b2c2b2643c448a4f597c33d6174d25712a021135077
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.