Stefan Dumitrescu commited on
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README.md CHANGED
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  license: apache-2.0
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  ---
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+ language: ro
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  license: apache-2.0
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  ---
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+
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+ # T5x-large-romanian
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+
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+ This is a pretrained-from-scratch [t5x](https://github.com/google-research/t5x) large model (783M parameters).
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+ Training was performed on a clean 80GB Romanian text corpus for 4M steps with these [scripts](https://github.com/dumitrescustefan/t5x_models). The model was trained with an encoder and decoder sequence length of 512.
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+
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+ #### **IMPORTANT** This model was pretrained on the span corruption LM task, meaning this model is **not usable** in any downstream task **without finetuning** first!
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+
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+ ### How to load a t5x model
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+
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+ ```python
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+ from transformers import T5Tokenizer, T5Model
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+
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+ tokenizer = T5Tokenizer.from_pretrained('dumitrescustefan/t5x-large-romanian')
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+ model = T5Model.from_pretrained('dumitrescustefan/t5x-large-romanian')
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+
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+ input_ids = tokenizer("Acesta este un test", return_tensors="pt").input_ids # Batch size 1
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+ decoder_input_ids = tokenizer("Acesta este", return_tensors="pt").input_ids # Batch size 1
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+
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+ # preprocess: Prepend decoder_input_ids with start token which is pad token for T5Model.
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+ # This is not needed for torch's T5ForConditionalGeneration as it does this internally using labels arg.
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+ decoder_input_ids = model._shift_right(decoder_input_ids)
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+
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+ # forward pass
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+ outputs = model(input_ids=input_ids, decoder_input_ids=decoder_input_ids)
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+ last_hidden_states = outputs.last_hidden_state
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+
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+ print(last_hidden_states.shape) # this will print [1, 3, 1024]
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+ ```
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+
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+ Remember to always sanitize your text! Replace ``ş`` and ``ţ`` cedilla-letters to comma-letters with :
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+ ```python
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+ text = text.replace("ţ", "ț").replace("ş", "ș").replace("Ţ", "Ț").replace("Ş", "Ș")
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+ ```
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+ because the model was **not** trained on cedilla ``ş`` and ``ţ``s. If you don't, you will have decreased performance due to ``<UNK>``s and increased number of tokens per word.
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+
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+ ### Acknowledgements
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+
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+ We'd like to thank [TPU Research Cloud](https://sites.research.google/trc/about/) for providing the TPUv4 cores we used to train these models!
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+
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+ ### Authors
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+
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+ Yours truly,
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+
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+ _[Stefan Dumitrescu](https://github.com/dumitrescustefan), [Mihai Ilie](https://github.com/iliemihai) and [Per Egil Kummervold](https://huggingface.co/north)_
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+ {"<pad>": 64100}
config.json ADDED
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+ {
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+ "_name_or_path": "checkpoint_4000000_fl",
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+ "architectures": [
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+ "MT5ForConditionalGeneration"
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+ ],
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+ "d_ff": 2816,
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+ "d_kv": 64,
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+ "decoder_start_token_id": 0,
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+ "dense_act_fn": "gelu_new",
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+ "dropout_rate": 0.1,
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+ "eos_token_id": 1,
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+ "feed_forward_proj": "gated-gelu",
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+ "initializer_factor": 1.0,
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+ "is_encoder_decoder": true,
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+ "is_gated_act": true,
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+ "layer_norm_epsilon": 1e-06,
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+ "model_type": "mt5",
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+ "num_decoder_layers": 24,
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+ "num_heads": 16,
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+ "num_layers": 24,
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+ "output_past": true,
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+ "pad_token_id": 0,
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+ "relative_attention_max_distance": 128,
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+ "tie_word_embeddings": false,
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+ "tokenizer_class": "T5Tokenizer",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.23.1",
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+ "use_cache": true,
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+ "vocab_size": 64000
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+ }
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