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| *This model was released on 2020-10-23 and added to Hugging Face Transformers on 2020-11-27.* | |
| <div style="float: right;"> | |
| <div class="flex flex-wrap space-x-1"> | |
| <img alt="PyTorch" src="https://img.shields.io/badge/PyTorch-DE3412?style=flat&logo=pytorch&logoColor=white"> | |
| </div> | |
| </div> | |
| # BARThez | |
| [BARThez](https://huggingface.co/papers/2010.12321) is a [BART](./bart) model designed for French language tasks. Unlike existing French BERT models, BARThez includes a pretrained encoder-decoder, allowing it to generate text as well. This model is also available as a multilingual variant, mBARThez, by continuing pretraining multilingual BART on a French corpus. | |
| You can find all of the original BARThez checkpoints under the [BARThez](https://huggingface.co/collections/dascim/barthez-670920b569a07aa53e3b6887) collection. | |
| > [!TIP] | |
| > This model was contributed by [moussakam](https://huggingface.co/moussakam). | |
| > Refer to the [BART](./bart) docs for more usage examples. | |
| The example below demonstrates how to predict the `<mask>` token with [`Pipeline`], [`AutoModel`], and from the command line. | |
| <hfoptions id="usage"> | |
| <hfoption id="Pipeline"> | |
| ```py | |
| import torch | |
| from transformers import pipeline | |
| pipeline = pipeline( | |
| task="fill-mask", | |
| model="moussaKam/barthez", | |
| dtype=torch.float16, | |
| device=0 | |
| ) | |
| pipeline("Les plantes produisent <mask> grâce à un processus appelé photosynthèse.") | |
| ``` | |
| </hfoption> | |
| <hfoption id="AutoModel"> | |
| ```py | |
| import torch | |
| from transformers import AutoModelForMaskedLM, AutoTokenizer | |
| tokenizer = AutoTokenizer.from_pretrained( | |
| "moussaKam/barthez", | |
| ) | |
| model = AutoModelForMaskedLM.from_pretrained( | |
| "moussaKam/barthez", | |
| dtype=torch.float16, | |
| device_map="auto", | |
| ) | |
| inputs = tokenizer("Les plantes produisent <mask> grâce à un processus appelé photosynthèse.", return_tensors="pt").to(model.device) | |
| with torch.no_grad(): | |
| outputs = model(**inputs) | |
| predictions = outputs.logits | |
| masked_index = torch.where(inputs['input_ids'] == tokenizer.mask_token_id)[1] | |
| predicted_token_id = predictions[0, masked_index].argmax(dim=-1) | |
| predicted_token = tokenizer.decode(predicted_token_id) | |
| print(f"The predicted token is: {predicted_token}") | |
| ``` | |
| </hfoption> | |
| <hfoption id="transformers CLI"> | |
| ```bash | |
| echo -e "Les plantes produisent <mask> grâce à un processus appelé photosynthèse." | transformers run --task fill-mask --model moussaKam/barthez --device 0 | |
| ``` | |
| </hfoption> | |
| </hfoptions> | |
| ## BarthezTokenizer | |
| [[autodoc]] BarthezTokenizer | |
| ## BarthezTokenizerFast | |
| [[autodoc]] BarthezTokenizerFast | |