Instructions to use google/flan-ul2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/flan-ul2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("google/flan-ul2") model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-ul2") - Notebooks
- Google Colab
- Kaggle
Seeking Recommendations for Pre-trained Models for Large-scale Paragraph Classification
Hello everyone,
I have a question regarding a classification task I'm working on, and I would appreciate your insights. I have a very large paragraph consisting of approximately 4,000 to 5,000 words, and I want to generate a sequence of outputs for this text. Specifically, I aim to classify the paragraph based on its content.
Given that I have access to two 32 GB GPUs, I'm wondering which pre-trained model would be best suited for this task. I would like to leverage the power of these GPUs to ensure efficient processing and accurate results.
If you have any recommendations or suggestions for pre-trained models that excel at sequence classification tasks, I would greatly appreciate your input. Thank you in advance for your help!