Text Classification
Transformers
Safetensors
English
bert
coping
emotions
microaggressions
text-embeddings-inference
Instructions to use coping-emotions/bert-coping-replies with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use coping-emotions/bert-coping-replies with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="coping-emotions/bert-coping-replies")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("coping-emotions/bert-coping-replies") model = AutoModelForSequenceClassification.from_pretrained("coping-emotions/bert-coping-replies", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from coping-emotions/bert-coping-replies: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/coping-emotions/bert-coping-replies/resolve/main/model.safetensors
- Command line
-
hf download hf://coping-emotions/bert-coping-replies/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/coping-emotions/bert-coping-replies/resolve/main/model.safetensors
438 MB
- Xet hash:
- e2d4acfaf8b6c823b7e3dcb24abce0e2a2e6a12926a317a8d3279adb27aba800
- Size of remote file:
- 438 MB
- SHA256:
- 856e2c566212ae2c46801791b6f347488fc9307922de2e11f3c32cc831b46ae9
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