Instructions to use mrm8488/funnel-transformer-intermediate-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/funnel-transformer-intermediate-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mrm8488/funnel-transformer-intermediate-mnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mrm8488/funnel-transformer-intermediate-mnli") model = AutoModelForSequenceClassification.from_pretrained("mrm8488/funnel-transformer-intermediate-mnli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c87e4126ab11d4700df05f701f4a2e20d36a8f08e5a77d454e1fec4d7606b350
- Size of remote file:
- 1.3 GB
- SHA256:
- fb751dd847d29df5865b438b9f517f06f758682e1905cd32c133d2e5abe75fec
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