Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use bwahyuh/digidawfinal_E5small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bwahyuh/digidawfinal_E5small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bwahyuh/digidawfinal_E5small")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bwahyuh/digidawfinal_E5small") model = AutoModelForSequenceClassification.from_pretrained("bwahyuh/digidawfinal_E5small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from bwahyuh/digidawfinal_E5small: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/bwahyuh/digidawfinal_E5small/resolve/main/tokenizer.json
- Command line
-
hf download hf://bwahyuh/digidawfinal_E5small/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/bwahyuh/digidawfinal_E5small/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- e4abd7c550586c7952a091b8b3d1e3e8e273621680819223d8114be54025c121
- Size of remote file:
- 17.1 MB
- SHA256:
- 66e2c4647474659095b757711e8aef0583d58dbb50e3349958ebc460a9cf4977
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