Text Classification
Transformers
PyTorch
ONNX
Safetensors
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use AdamCodd/tinybert-emotion-balanced with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AdamCodd/tinybert-emotion-balanced with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AdamCodd/tinybert-emotion-balanced")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AdamCodd/tinybert-emotion-balanced") model = AutoModelForSequenceClassification.from_pretrained("AdamCodd/tinybert-emotion-balanced", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c6112ba572009ef3faeb491999d9bdb39373d7797b9f2450fd79cf7681821fb4
- Size of remote file:
- 17.6 MB
- SHA256:
- cb62a10254dcfb5e4fc460d7b338e1cbc280ed689f6af441b3670fac9c8f9b32
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