Instructions to use Jellevdl/checkpoint-20000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jellevdl/checkpoint-20000 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Jellevdl/checkpoint-20000")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Jellevdl/checkpoint-20000") model = AutoModelForQuestionAnswering.from_pretrained("Jellevdl/checkpoint-20000") - 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 sha256:995091da724975d402838bd1164ef76827f594659f1e8aee2cefb282bfe065ee
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size 435600272
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