Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use coderSounak/finetuning-hs-model-bert-multilingual with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use coderSounak/finetuning-hs-model-bert-multilingual with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="coderSounak/finetuning-hs-model-bert-multilingual")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("coderSounak/finetuning-hs-model-bert-multilingual") model = AutoModelForSequenceClassification.from_pretrained("coderSounak/finetuning-hs-model-bert-multilingual", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from coderSounak/finetuning-hs-model-bert-multilingual: direct link, hf CLI and curl.
- Browser
- Download file 711 MB
-
https://huggingface.co/coderSounak/finetuning-hs-model-bert-multilingual/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://coderSounak/finetuning-hs-model-bert-multilingual/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/coderSounak/finetuning-hs-model-bert-multilingual/resolve/main/pytorch_model.bin
711 MB
- Xet hash:
- 3925ce1682b9464abb872cc334875516d85a3c2b0ee159231256fef36cbdfdba
- Size of remote file:
- 711 MB
- SHA256:
- 2a8871d17093fa6a5223fb1afcadf263058f88f5a9b21099e466998b5d0ab814
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