Instructions to use kristinehara/tmp_trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kristinehara/tmp_trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="kristinehara/tmp_trainer")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("kristinehara/tmp_trainer") model = AutoModel.from_pretrained("kristinehara/tmp_trainer") - 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 sha256:8437f4788a4d9f8c5879c5e2d85ce857004c36327897511e66776771c6e39da1
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size 478740376
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