Instructions to use d4data/environmental-due-diligence-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use d4data/environmental-due-diligence-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="d4data/environmental-due-diligence-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("d4data/environmental-due-diligence-model") model = AutoModelForSequenceClassification.from_pretrained("d4data/environmental-due-diligence-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -35,6 +35,6 @@ classifier("At the every month post-injection monitoring event, TCE, carbon tetr
|
|
| 35 |
```
|
| 36 |
|
| 37 |
## Author
|
| 38 |
-
This model is part of the Research topic "Environmental Due Diligence" conducted by Deepak John Reji, Afreen Aman
|
| 39 |
-
> Environmental Due Diligence, (2020),
|
| 40 |
|
|
|
|
| 35 |
```
|
| 36 |
|
| 37 |
## Author
|
| 38 |
+
This model is part of the Research topic "Environmental Due Diligence" conducted by Deepak John Reji, Afreen Aman. If you use this work (code, model or dataset), please cite as:
|
| 39 |
+
> Environmental Due Diligence, (2020), https://www.sciencedirect.com/science/article/pii/S2665963822001117
|
| 40 |
|