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Original Code: https://github.com/pytorch/fairseq/tree/master/examples/mbart Docs: https://huggingface.co/transformers/master/model_doc/mbart.html Finetuning Code: examples/seq2seq/finetune.py (as of Aug 20, 2020)
It scores BLEU 28.1 without post processing and BLEU 38 with postprocessing. Instructions in `romanian_postprocessing.md`
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Distilled MetaCLIP 2 (worldwide) was presented in MetaCLIP 2: A Worldwide Scaling Recipe. This checkpoint corresponds to "ViT-B-16-worldwide" of the original implementation. In case you want to perform pre- and postprocessing yourself, you can use the `AutoModel` API:
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Adjust provider, category or input/output filters. New models are added continuously.
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Uses collected, comparable USD-per-million-token rates. Snapshots exclude cache discounts, tiers, extra reasoning output and taxes. Check current source prices.
Separate input, output and cache rates, then estimate the same workload. Image, audio and video rates may use items, duration or resolution rather than tokens.
Not necessarily. Check each version’s license, commercial restrictions and policies. Self-hosting also incurs compute and maintenance costs.
Rankings depend on tasks, versions and methods. Compare accuracy, latency, reliability and costs on your own workload.
