Instructions to use pulp/CHILDES-ParentBERTo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pulp/CHILDES-ParentBERTo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="pulp/CHILDES-ParentBERTo")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("pulp/CHILDES-ParentBERTo") model = AutoModelForMaskedLM.from_pretrained("pulp/CHILDES-ParentBERTo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from pulp/CHILDES-ParentBERTo: direct link, hf CLI and curl.
- Browser
- Download file 276 MB
-
https://huggingface.co/pulp/CHILDES-ParentBERTo/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://pulp/CHILDES-ParentBERTo/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/pulp/CHILDES-ParentBERTo/resolve/main/flax_model.msgpack
276 MB
- Xet hash:
- 29cfb952cc492c0b16075bff00dfecdc3204b0081aebc2e98caed54e7f8d5312
- Size of remote file:
- 276 MB
- SHA256:
- 19079a6773b625912f30c734e7bed56b46448ace88a457c994422e802b51da3a
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