Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use flowfree/bert-finetuned-cryptos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flowfree/bert-finetuned-cryptos with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="flowfree/bert-finetuned-cryptos")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("flowfree/bert-finetuned-cryptos") model = AutoModelForSequenceClassification.from_pretrained("flowfree/bert-finetuned-cryptos") - 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 sha256:1dd76ea3077d96f9d0b18d54c17e3c08a60a42771aba61538c2e47c5c72c3261
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size 437965908
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