Instructions to use maxbeettww/roberta-MeSH-lora-without-duplicate-path with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use maxbeettww/roberta-MeSH-lora-without-duplicate-path with PEFT:
Task type is invalid.
- Transformers
How to use maxbeettww/roberta-MeSH-lora-without-duplicate-path with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("maxbeettww/roberta-MeSH-lora-without-duplicate-path", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download train_log.csv from maxbeettww/roberta-MeSH-lora-without-duplicate-path: direct link, hf CLI and curl.
- Browser
- Download file 463 Bytes
-
https://huggingface.co/maxbeettww/roberta-MeSH-lora-without-duplicate-path/resolve/main/train_log.csv
- Command line
-
hf download hf://maxbeettww/roberta-MeSH-lora-without-duplicate-path/train_log.csv
-
curl -L -o train_log.csv https://huggingface.co/maxbeettww/roberta-MeSH-lora-without-duplicate-path/resolve/main/train_log.csv
463 Bytes
| epoch,train_loss,val_loss | |
| 1,0.01731098252816581,0.01604353136240022 | |
| 2,0.013366963278279714,0.014053670106642345 | |
| 3,0.012405841278663234,0.013696867510426178 | |
| 4,0.011644153810377955,0.013898261968713643 | |
| 5,0.010800416682985692,0.011461490960811565 | |
| 6,0.01006045886965499,0.010559050928253228 | |
| 7,0.009253272447451635,0.010183120465605084 | |
| 8,0.008544183403884223,0.009594380102459905 | |
| 9,0.007975867728515752,0.00852605485434789 | |
| 10,0.007436476772464326,0.008271555498198692 | |