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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("flowfree/bert-finetuned-cryptos") model = AutoModelForSequenceClassification.from_pretrained("flowfree/bert-finetuned-cryptos", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from flowfree/bert-finetuned-cryptos: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/flowfree/bert-finetuned-cryptos/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://flowfree/bert-finetuned-cryptos/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/flowfree/bert-finetuned-cryptos/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 5a8ae676166449928b8aa40a0b451c68aa4c3d335e1f5eecbd7b1af78e8581cf
- Size of remote file:
- 438 MB
- SHA256:
- fcda6c73c9f3d348c0992ffe41af02761ffea012d1c2efd541961895006b2636
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