Text Classification
Transformers
PyTorch
English
bert
Twitter
Climate Change
text-embeddings-inference
Instructions to use Climate-TwitterBERT/Climate-TwitterBERT-step1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Climate-TwitterBERT/Climate-TwitterBERT-step1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Climate-TwitterBERT/Climate-TwitterBERT-step1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Climate-TwitterBERT/Climate-TwitterBERT-step1") model = AutoModelForSequenceClassification.from_pretrained("Climate-TwitterBERT/Climate-TwitterBERT-step1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 25a6034121081fd5f9c2a4d3a4f9d1c8f25b235f2fde2ff81ed6f5f1726bfd35
- Size of remote file:
- 1.34 GB
- SHA256:
- addfaad9896b393ccb1589b035f30960254b446463e1ad3ebb0d2347c203164f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.