google-research-datasets/go_emotions
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How to use poom-sci/bert-base-uncased-multi-emotion with Transformers:
# Use a pipeline as a high-level helper
# Warning: Pipeline type "translation" is no longer supported in transformers v5.
# You must load the model directly (see below) or downgrade to v4.x with:
# pip install "transformers<5.0.0"
from transformers import pipeline
pipe = pipeline("translation", model="poom-sci/bert-base-uncased-multi-emotion") # pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("poom-sci/bert-base-uncased-multi-emotion")
model = AutoModelForSequenceClassification.from_pretrained("poom-sci/bert-base-uncased-multi-emotion", device_map="auto")# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("poom-sci/bert-base-uncased-multi-emotion")
model = AutoModelForSequenceClassification.from_pretrained("poom-sci/bert-base-uncased-multi-emotion", device_map="auto")created for study
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("translation", model="poom-sci/bert-base-uncased-multi-emotion")