Instructions to use hf-tiny-model-private/tiny-random-FlaubertForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-FlaubertForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-tiny-model-private/tiny-random-FlaubertForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-FlaubertForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-FlaubertForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
File size: 132 Bytes
edb9e91 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:b564d5303c5ab0a60ef99d814752e2a56459e26578a2df4d000d4c718670a88d
size 8974272
|