Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use coderSounak/finetuning-sentiment-model-bert-multilingual with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use coderSounak/finetuning-sentiment-model-bert-multilingual with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="coderSounak/finetuning-sentiment-model-bert-multilingual")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("coderSounak/finetuning-sentiment-model-bert-multilingual") model = AutoModelForSequenceClassification.from_pretrained("coderSounak/finetuning-sentiment-model-bert-multilingual", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from coderSounak/finetuning-sentiment-model-bert-multilingual: direct link, hf CLI and curl.
- Browser
- Download file 3.44 kB
-
https://huggingface.co/coderSounak/finetuning-sentiment-model-bert-multilingual/resolve/main/training_args.bin
- Command line
-
hf download hf://coderSounak/finetuning-sentiment-model-bert-multilingual/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/coderSounak/finetuning-sentiment-model-bert-multilingual/resolve/main/training_args.bin
3.44 kB
- Xet hash:
- f4882731889c2d51cefc57259d4b550e8c73210032cafe6daf62b2cd8e74426a
- Size of remote file:
- 3.44 kB
- SHA256:
- d1d632430c17920b1ebccb74d9b349639748eaba10ef11d76da204bd16105a97
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.