Text Classification
Transformers
Safetensors
English
bert
multi-label
go-emotions
huggingface
text-embeddings-inference
Instructions to use codewithdark/bert-Gomotions with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use codewithdark/bert-Gomotions with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="codewithdark/bert-Gomotions")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("codewithdark/bert-Gomotions") model = AutoModelForSequenceClassification.from_pretrained("codewithdark/bert-Gomotions", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b6daa28f806a5e627e6c3df2cfcd6a2ef49b804cc6f004fccffbe9516728f2b1
- Size of remote file:
- 438 MB
- SHA256:
- 9727d14bd1e23577d79a98632925ea539991c1aab0511717d8a7b417770b58be
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