| --- |
| license: apache-2.0 |
| base_model: answerdotai/ModernBERT-large |
| language: |
| - en |
| tags: |
| - fact-checking |
| - context-pruning |
| - evidence-retrieval |
| --- |
| |
| # evidenceprune-modernbert-large |
|
|
| evidenceprune is a lightweight context-pruning model fine-tuned for fact checking. Given a |
| claim and a web page, it marks the sentences a fact-checker would need. |
|
|
| This checkpoint is a 0.4B encoder fine-tuned from ModernBERT-large as a token classifier. |
|
|
| ## Usage |
|
|
| ``` |
| pip install git+https://github.com/ofbread/evidenceprune |
| ``` |
|
|
| ```python |
| from evidenceprune import Pruner |
| |
| kept = Pruner("ofbread/evidenceprune-modernbert-large").prune(claim, documents) |
| ``` |
|
|
|
|
| ## Input |
|
|
| `Pruner(model, threshold=None, device=None)` loads the model. |
| `prune(claim, documents, requirements=None, claim_date="", speaker="", cap_windows=16, stop_after_empty=2, doc_ceiling=12000)` reads the pages. |
|
|
| | parameter | type | meaning | |
| |---|---|---| |
| | `claim` | str | the claim being checked | |
| | `documents` | list of `{"text": str, "title": str, "url": str}` | the pages; `title` and `url` are optional but the model was trained with them | |
| | `claim_date` | str, optional | when the claim was made, `YYYY-MM-DD` | |
| | `speaker` | str, optional | who made the claim | |
| | `requirements` | list of str, optional | what must be established to check the claim | |
| | `threshold` | float, default 0.3458 | a sentence is kept when its P(keep) is at or above this | |
| | `cap_windows` | int, default 16 | read at most this many windows of 48 sentences (at most 10,000 characters each) per page | |
| | `stop_after_empty` | int, default 2 | stop reading a page after this many consecutive windows with nothing kept | |
| | `doc_ceiling` | int, default 12000 | a page contributes at most this many characters | |
| | `device` | str, optional | `cuda` or `cpu`| |
|
|
| ## Output |
|
|
| `prune` returns one result per document, in order: |
|
|
| | field | type | meaning | |
| |---|---|---| |
| | `text` | str | the kept sentences, in page order, gaps marked with `[…]` | |
| | `kept` | list of (start, end) | offsets of each kept sentence in the document's `text` | |
| | `sentences` | list of str | the same sentences as strings | |
| | `probs` | dict, sentence index → float | P(keep) for every sentence the model read | |
| | `title_kept` | bool | the title is read as the page's first sentence | |
| | `windows_read`, `n_windows` | int | windows the model read, windows in the page | |
| | `stopped_early` | bool | whether the stop rule ended the read | |
|
|
