Instructions to use avacaondata/maria-exist22-task1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use avacaondata/maria-exist22-task1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="avacaondata/maria-exist22-task1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("avacaondata/maria-exist22-task1") model = AutoModelForSequenceClassification.from_pretrained("avacaondata/maria-exist22-task1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from avacaondata/maria-exist22-task1: direct link, hf CLI and curl.
- Browser
- Download file 997 MB
-
https://huggingface.co/avacaondata/maria-exist22-task1/resolve/main/optimizer.pt
- Command line
-
hf download hf://avacaondata/maria-exist22-task1/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/avacaondata/maria-exist22-task1/resolve/main/optimizer.pt
997 MB
- Xet hash:
- e0f04adfaf86aa5a1fcabecebb361f68b5cf4d70e267cd23f7a8b673163b94b6
- Size of remote file:
- 997 MB
- SHA256:
- 5fc01a9de9b446ec5027b5bd05a01bb225b1fdcff7af0b125eb6cdce78f01ca1
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