Summarization
Transformers
Safetensors
English
led
text2text-generation
Summarization
Longformer
LED
Fine-Tuned
Abstractive
Scientific
seq2seq
english
attention
text-processing
NLP
beam-search
Instructions to use yashrane2904/LED_Finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yashrane2904/LED_Finetuned 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="yashrane2904/LED_Finetuned")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("yashrane2904/LED_Finetuned") model = AutoModelForSeq2SeqLM.from_pretrained("yashrane2904/LED_Finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from yashrane2904/LED_Finetuned: direct link, hf CLI and curl.
- Browser
- Download file 1.14 kB
-
https://huggingface.co/yashrane2904/LED_Finetuned/resolve/main/config.json
- Command line
-
hf download hf://yashrane2904/LED_Finetuned/config.json
-
curl -L -o config.json https://huggingface.co/yashrane2904/LED_Finetuned/resolve/main/config.json
1.14 kB
| { | |
| "_name_or_path": "/content/LED_finetuned", | |
| "activation_dropout": 0.0, | |
| "activation_function": "gelu", | |
| "architectures": [ | |
| "LEDForConditionalGeneration" | |
| ], | |
| "attention_dropout": 0.0, | |
| "attention_window": [ | |
| 1024, | |
| 1024, | |
| 1024, | |
| 1024, | |
| 1024, | |
| 1024 | |
| ], | |
| "bos_token_id": 0, | |
| "classif_dropout": 0.0, | |
| "classifier_dropout": 0.0, | |
| "d_model": 768, | |
| "decoder_attention_heads": 12, | |
| "decoder_ffn_dim": 3072, | |
| "decoder_layerdrop": 0.0, | |
| "decoder_layers": 6, | |
| "decoder_start_token_id": 2, | |
| "dropout": 0.1, | |
| "encoder_attention_heads": 12, | |
| "encoder_ffn_dim": 3072, | |
| "encoder_layerdrop": 0.0, | |
| "encoder_layers": 6, | |
| "eos_token_id": 2, | |
| "id2label": { | |
| "0": "LABEL_0", | |
| "1": "LABEL_1", | |
| "2": "LABEL_2" | |
| }, | |
| "init_std": 0.02, | |
| "is_encoder_decoder": true, | |
| "label2id": { | |
| "LABEL_0": 0, | |
| "LABEL_1": 1, | |
| "LABEL_2": 2 | |
| }, | |
| "max_decoder_position_embeddings": 1024, | |
| "max_encoder_position_embeddings": 16384, | |
| "model_type": "led", | |
| "num_hidden_layers": 6, | |
| "pad_token_id": 1, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.38.2", | |
| "use_cache": false, | |
| "vocab_size": 50265 | |
| } | |