Instructions to use Jingya/tiny-random-bert-remote-code with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jingya/tiny-random-bert-remote-code with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Jingya/tiny-random-bert-remote-code")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Jingya/tiny-random-bert-remote-code") model = AutoModel.from_pretrained("Jingya/tiny-random-bert-remote-code") - Notebooks
- Google Colab
- Kaggle
Commit ·
fe5dccb
1
Parent(s): b05d834
Adding `safetensors` variant of this model (#1)
Browse files- Adding `safetensors` variant of this model (db5d8988ddeb0d4a4a80f8e5133a3f5d9e5ea18f)
Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:d3852eaaa77bb7d0941b3a04cd31483e9a5d0fb430b1b24cf9a5513f0ead2e0d
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size 364988
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