Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use thenewsupercell/BertEmotionV1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thenewsupercell/BertEmotionV1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="thenewsupercell/BertEmotionV1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("thenewsupercell/BertEmotionV1") model = AutoModelForSequenceClassification.from_pretrained("thenewsupercell/BertEmotionV1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from thenewsupercell/BertEmotionV1: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/thenewsupercell/BertEmotionV1/resolve/main/training_args.bin
- Command line
-
hf download hf://thenewsupercell/BertEmotionV1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/thenewsupercell/BertEmotionV1/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- 3ddb9b1df3b2f2301fd549317629d9c77cf0df109f48611af26ebcd87045247d
- Size of remote file:
- 5.3 kB
- SHA256:
- bc363d30908c83d25708b21a7798211d07f72fea165b00a5aaceaeec59167661
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