Summarization
Transformers
PyTorch
Safetensors
English
led
text2text-generation
Eval Results (legacy)
Instructions to use AlgorithmicResearchGroup/led_large_16384_arxiv_summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AlgorithmicResearchGroup/led_large_16384_arxiv_summarization with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("summarization", model="AlgorithmicResearchGroup/led_large_16384_arxiv_summarization")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("AlgorithmicResearchGroup/led_large_16384_arxiv_summarization") model = AutoModelForSeq2SeqLM.from_pretrained("AlgorithmicResearchGroup/led_large_16384_arxiv_summarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "best_metric": null, | |
| "best_model_checkpoint": null, | |
| "epoch": 0.5333333333333333, | |
| "global_step": 500, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "epoch": 0.11, | |
| "learning_rate": 4.4983991462113126e-05, | |
| "loss": 2.4818, | |
| "step": 100 | |
| }, | |
| { | |
| "epoch": 0.21, | |
| "learning_rate": 3.970117395944504e-05, | |
| "loss": 2.2118, | |
| "step": 200 | |
| }, | |
| { | |
| "epoch": 0.32, | |
| "learning_rate": 3.436499466382071e-05, | |
| "loss": 2.1462, | |
| "step": 300 | |
| }, | |
| { | |
| "epoch": 0.43, | |
| "learning_rate": 2.9028815368196372e-05, | |
| "loss": 2.1053, | |
| "step": 400 | |
| }, | |
| { | |
| "epoch": 0.53, | |
| "learning_rate": 2.3692636072572037e-05, | |
| "loss": 2.075, | |
| "step": 500 | |
| } | |
| ], | |
| "max_steps": 937, | |
| "num_train_epochs": 1, | |
| "total_flos": 3.07105194049536e+17, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |