Instructions to use imaneb942/MNLP_M3_document_encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use imaneb942/MNLP_M3_document_encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="imaneb942/MNLP_M3_document_encoder")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("imaneb942/MNLP_M3_document_encoder") model = AutoModel.from_pretrained("imaneb942/MNLP_M3_document_encoder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 197 Bytes
35db0bb | 1 2 3 4 5 6 7 | {
"word_embedding_dimension": 1024,
"pooling_mode_cls_token": false,
"pooling_mode_mean_tokens": true,
"pooling_mode_max_tokens": false,
"pooling_mode_mean_sqrt_len_tokens": false
} |