Instructions to use spneshaei/bert-base-uncased-mr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use spneshaei/bert-base-uncased-mr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="spneshaei/bert-base-uncased-mr")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("spneshaei/bert-base-uncased-mr") model = AutoModelForSequenceClassification.from_pretrained("spneshaei/bert-base-uncased-mr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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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:f65e307459f2d30ba28754f301d3d2ffc718c5bfa60f3217bb64b46cb36f61a7
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size 437962832
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