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* Add `CodeLlamaTokenizer` * Add `codellama` for testing * Update default quantization settings * Refactor `PretrainedModel` * Remove unnecessary error message * Update llama-code-tokenizer test * Add support for `GPTNeoX` models * Fix `GPTNeoXPreTrainedModel` config * Add support for `GPTJ` models * Add support for `WavLM` models * Update list of supported models - CodeLlama - GPT NeoX - GPT-J - WavLM * Add support for XLM models * Add support for `ResNet` models * Add support for `BeiT` models * Fix casing of `BeitModel` * Remove duplicate code * Update variable name * Remove `ts-ignore` * Remove unnecessary duplication * Update demo model sizes * [demo] Update default summarization parameters * Update default quantization parameters for new models * Remove duplication in mapping * Update list of supported marian models * Add support for `CamemBERT` models * Add support for `MBart` models * Add support for `OPT` models * Add `MBartTokenizer` and `MBart50Tokenizer` * Add example of multilingual translation with MBart models * Add `CamembertTokenizer` * Add support for `HerBERT` models * Add support for `XLMTokenizer` * Fix `fuse_unk` config * Do not remove duplicate keys for `Unigram` models See https://huggingface.co/camembert-base for an example of a Unigram tokenizer that has two tokens with the same value (`<unk>`) * Update HerBERT supported model text * Update generate_tests.py * Update list of supported models * Use enum object instead of classes for model types Fixes https://github.com/xenova/transformers.js/issues/283 * Add link to issue * Update dependencies for unit tests * Add `sentencepiece` as a testing requirement * Add `protobuf` to test dependency * Remove duplicated models to test |
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