Instructions to use JAWCF/spladeX-TT-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JAWCF/spladeX-TT-es with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="JAWCF/spladeX-TT-es")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("JAWCF/spladeX-TT-es") model = AutoModelForMaskedLM.from_pretrained("JAWCF/spladeX-TT-es") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:7e4dc06383d380f24a0d9940d8ccceaea88db9246922fe4b6e991ede8c9c0acb
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size 541795756
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