Instructions to use Carick/albert-base-v2-wordnet_dataset_three-fine-tuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Carick/albert-base-v2-wordnet_dataset_three-fine-tuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Carick/albert-base-v2-wordnet_dataset_three-fine-tuned")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Carick/albert-base-v2-wordnet_dataset_three-fine-tuned") model = AutoModelForSequenceClassification.from_pretrained("Carick/albert-base-v2-wordnet_dataset_three-fine-tuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download spiece.model from Carick/albert-base-v2-wordnet_dataset_three-fine-tuned: direct link, hf CLI and curl.
- Browser
- Download file 760 kB
-
https://huggingface.co/Carick/albert-base-v2-wordnet_dataset_three-fine-tuned/resolve/main/spiece.model
- Command line
-
hf download hf://Carick/albert-base-v2-wordnet_dataset_three-fine-tuned/spiece.model
-
curl -L -o spiece.model https://huggingface.co/Carick/albert-base-v2-wordnet_dataset_three-fine-tuned/resolve/main/spiece.model
760 kB
- Xet hash:
- 555f23db1f24d7d57fbdd8a2683a72c22c0e687314fd1c2a55e2e4635c14ffee
- Size of remote file:
- 760 kB
- SHA256:
- fefb02b667a6c5c2fe27602d28e5fb3428f66ab89c7d6f388e7c8d44a02d0336
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