Instructions to use ElMad/likeable-donkey-705 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ElMad/likeable-donkey-705 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ElMad/likeable-donkey-705")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ElMad/likeable-donkey-705") model = AutoModelForSequenceClassification.from_pretrained("ElMad/likeable-donkey-705", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 76ea4178c33bf7f7288c8d0c017d67e821b152a58776acf6a3bd7a06e8ec8423
- Size of remote file:
- 283 MB
- SHA256:
- d54c4898b463b12722af37f3d7c0c2693bb7e0ade88f46b454383f34504f018b
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