Instructions to use yuzc19/bert-base-uncased-data-influence-model-lambada with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yuzc19/bert-base-uncased-data-influence-model-lambada with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yuzc19/bert-base-uncased-data-influence-model-lambada")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("yuzc19/bert-base-uncased-data-influence-model-lambada") model = AutoModelForSequenceClassification.from_pretrained("yuzc19/bert-base-uncased-data-influence-model-lambada") - Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
52c8b98 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:b8198ab27263cdbe184ccd1706ac275cc7ff225ac986292f16e2cc0a712632ca
size 438000878
|