Text Classification
Transformers
PyTorch
Safetensors
English
roberta
climate
text-embeddings-inference
Instructions to use climatebert/distilroberta-base-climate-specificity with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use climatebert/distilroberta-base-climate-specificity with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="climatebert/distilroberta-base-climate-specificity")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("climatebert/distilroberta-base-climate-specificity") model = AutoModelForSequenceClassification.from_pretrained("climatebert/distilroberta-base-climate-specificity", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Add tag to model card metadata
To help make your model more discoverable to domain experts, I suggest adding a `climate` tag to the metadata for your model.685e146
-
Create README.md
e1b45c5
-
Update tokenizer based on new language model
a21cb67 -
Update model based on new language model and new training samples
0d1c244
-
Update model based on new language model and new training samples
e9d7549
-
add tokenizer
bae9bbf -
add model
2a5ad19
-
initial commit
50fa151