Instructions to use divers/flan-base-req-extractor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use divers/flan-base-req-extractor with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("divers/flan-base-req-extractor") model = AutoModelForSeq2SeqLM.from_pretrained("divers/flan-base-req-extractor", device_map="auto") - Notebooks
- Google Colab
- Kaggle
|
Download README.md from divers/flan-base-req-extractor: direct link, hf CLI and curl.
- Browser
- Download file 2.46 kB
-
https://huggingface.co/divers/flan-base-req-extractor/resolve/main/README.md
- Command line
-
hf download hf://divers/flan-base-req-extractor/README.md
-
curl -L -o README.md https://huggingface.co/divers/flan-base-req-extractor/resolve/main/README.md
2.46 kB
| html''' | |
| <table> | |
| <tr> | |
| <th>Epoch</th> | |
| <th>Training Loss</th> | |
| <th>Validation Loss</th> | |
| <th>Rouge1</th> | |
| <th>Rouge2</th> | |
| <th>Rougel</th> | |
| <th>Rougelsum</th> | |
| <th>Gen Len</th> | |
| </tr> | |
| <tr> | |
| <td>0</td> | |
| <td>0.357300</td> | |
| <td>0.280200</td> | |
| <td>0.732700</td> | |
| <td>0.685700</td> | |
| <td>0.695100</td> | |
| <td>0.700500</td> | |
| <td>303.733300</td> | |
| </tr> | |
| <tr> | |
| <td>2</td> | |
| <td>0.257200</td> | |
| <td>0.244938</td> | |
| <td>0.742900</td> | |
| <td>0.702100</td> | |
| <td>0.712600</td> | |
| <td>0.717700</td> | |
| <td>330.200000</td> | |
| </tr> | |
| <tr> | |
| <td>2</td> | |
| <td>0.229900</td> | |
| <td>0.230673</td> | |
| <td>0.789800</td> | |
| <td>0.747500</td> | |
| <td>0.759500</td> | |
| <td>0.765300</td> | |
| <td>267.666700</td> | |
| </tr> | |
| <tr> | |
| <td>4</td> | |
| <td>0.209900</td> | |
| <td>0.213156</td> | |
| <td>0.800300</td> | |
| <td>0.759900</td> | |
| <td>0.766400</td> | |
| <td>0.771700</td> | |
| <td>274.466700</td> | |
| </tr> | |
| <tr> | |
| <td>4</td> | |
| <td>0.196200</td> | |
| <td>0.207821</td> | |
| <td>0.782800</td> | |
| <td>0.745000</td> | |
| <td>0.754900</td> | |
| <td>0.756200</td> | |
| <td>288.333300</td> | |
| </tr> | |
| <tr> | |
| <td>6</td> | |
| <td>0.183900</td> | |
| <td>0.203908</td> | |
| <td>0.752000</td> | |
| <td>0.715000</td> | |
| <td>0.726300</td> | |
| <td>0.727100</td> | |
| <td>309.755600</td> | |
| </tr> | |
| <tr> | |
| <td>6</td> | |
| <td>0.174500</td> | |
| <td>0.203386</td> | |
| <td>0.786100</td> | |
| <td>0.743400</td> | |
| <td>0.750800</td> | |
| <td>0.756200</td> | |
| <td>252.422200</td> | |
| </tr> | |
| <tr> | |
| <td>8</td> | |
| <td>0.165500</td> | |
| <td>0.190161</td> | |
| <td>0.771100</td> | |
| <td>0.733500</td> | |
| <td>0.735600</td> | |
| <td>0.740400</td> | |
| <td>292.288900</td> | |
| </tr> | |
| <tr> | |
| <td>8</td> | |
| <td>0.158300</td> | |
| <td>0.192600</td> | |
| <td>0.774900</td> | |
| <td>0.737300</td> | |
| <td>0.743300</td> | |
| <td>0.744300</td> | |
| <td>285.800000</td> | |
| </tr> | |
| <tr> | |
| <td>9</td> | |
| <td>0.152200</td> | |
| <td>0.192426</td> | |
| <td>0.795200</td> | |
| <td>0.758900</td> | |
| <td>0.754700</td> | |
| <td>0.759000</td> | |
| <td>284.266700</td> | |
| </tr> | |
| <tr> | |
| <td>15</td> | |
| <td>0.124400</td> | |
| <td>0.182381</td> | |
| <td>0.787800</td> | |
| <td>0.742800</td> | |
| <td>0.745100</td> | |
| <td>0.746900</td> | |
| <td>274.533300</td> | |
| </tr> | |
| <tr> | |
| <td>17</td> | |
| <td>0.120300</td> | |
| <td>0.183192</td> | |
| <td>0.779400</td> | |
| <td>0.739000</td> | |
| <td>0.734500</td> | |
| <td>0.739300</td> | |
| <td>289.266700</td> | |
| </tr> | |
| </table> | |
| ''' |