[BART] add bart-large-xsum weights #3422
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@@ Coverage Diff @@
## master #3422 +/- ##
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- Coverage 77.80% 77.79% -0.01%
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Files 100 100
Lines 17051 17051
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- Hits 13266 13265 -1
- Misses 3785 3786 +1
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thomwolf
reviewed
Mar 26, 2020
src/transformers/modeling_bart.py
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| base_model_prefix = "model" | ||
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| def __init__(self, config: BartConfig): | ||
| def __init__(self, config: BartConfig, base_model=None): |
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thomwolf
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Mar 26, 2020
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torch.hub. Finetuning with fairseq and then converting to huggingface should work. I also cleaned it up a bit(num_beams=6, length_penalty=1., min_length=11, max_length=62Context:
These weights are from bart finetuned on the XSum abstractive summarization challenge, which encourages shorter (more abstractive) summaries. It achieves state of the art.
Discussion: