Instructions to use mllm-dev/merge_diff_data_IMDB_10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mllm-dev/merge_diff_data_IMDB_10 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mllm-dev/merge_diff_data_IMDB_10")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mllm-dev/merge_diff_data_IMDB_10") model = AutoModelForSequenceClassification.from_pretrained("mllm-dev/merge_diff_data_IMDB_10", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 45b5df6d218bbb1076b9446f4e0e812286e2c1a782bf0614381b5ec4f8881c69
- Size of remote file:
- 498 MB
- SHA256:
- 9bc5a9b7a4786689497bc6bd6cd4d9ba29ecc350d1ca5755634437dbda35eaf9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.