Instructions to use avichr/hebEMO_fear with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use avichr/hebEMO_fear with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="avichr/hebEMO_fear")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("avichr/hebEMO_fear") model = AutoModelForSequenceClassification.from_pretrained("avichr/hebEMO_fear", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from avichr/hebEMO_fear: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/avichr/hebEMO_fear/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://avichr/hebEMO_fear/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/avichr/hebEMO_fear/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 92dad0c3dfa8aeeb5b1b89b5ff836aa7dc45c1e3b84f77ace8e0099f5a01fe2c
- Size of remote file:
- 438 MB
- SHA256:
- acffd9cb9b83580550c4049647d0fcef9c2323a3feb50ebeb82676c2b6fb35d5
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