Instructions to use osiria/minilm-l12-h384-italian-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use osiria/minilm-l12-h384-italian-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="osiria/minilm-l12-h384-italian-cased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("osiria/minilm-l12-h384-italian-cased") model = AutoModelForMaskedLM.from_pretrained("osiria/minilm-l12-h384-italian-cased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| license: mit | |
| language: | |
| - it | |
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| <span class="vertical-text" style="background-color:lightblue;border-radius: 3px;padding: 3px;"> Model: MiniLM</span> | |
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| <h3>Model description</h3> | |
| This is a <b>MiniLMv2</b> <b>[1]</b> model for the <b>Italian</b> language, obtained using <b>mMiniLMv2</b> ([L12xH384 mMiniLMv2](https://github.com/microsoft/unilm/tree/master/minilm)) as a starting point and focusing it on the Italian language by modifying the embedding layer | |
| (as in <b>[2]</b>, computing document-level frequencies over the <b>Wikipedia</b> dataset) | |
| The resulting model has 33M parameters, a vocabulary of 30.498 tokens, and a size of ~130 MB. | |
| <h3>References</h3> | |
| [1] https://arxiv.org/abs/2012.15828 | |
| [2] https://arxiv.org/abs/2010.05609 | |
| <h3>License</h3> | |
| The model is released under <b>MIT</b> license |