Instructions to use PartiallyTyped/answerable_tydiqa_lm_pretrained_japanese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PartiallyTyped/answerable_tydiqa_lm_pretrained_japanese with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="PartiallyTyped/answerable_tydiqa_lm_pretrained_japanese")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("PartiallyTyped/answerable_tydiqa_lm_pretrained_japanese") model = AutoModel.from_pretrained("PartiallyTyped/answerable_tydiqa_lm_pretrained_japanese") - Notebooks
- Google Colab
- Kaggle
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Check out the documentation for more information.
ReadMe
This is a pretrained model based on rinna/japanese-gpt2-small that has been trained on copenlu/answerable_tydiqa, specifically the text field of the Japanese samples for 2 epochs.
To use the pretrained head, use: AutoModelForCausalLM.from_pretrained.
from transformers import AutoModelForCausalLM, T5Tokenizer
model_path = "PartiallyTyped/answerable_tydiqa_lm_pretrained_japanese"
model = AutoModelForCausalLM.from_pretrained(path)
tokenizer = T5Tokenizer.from_pretrained(path)
tokenizer.do_lower_case = True # due to some bug of tokenizer config loading
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