Summarization
Transformers
PyTorch
Safetensors
Enawené-Nawé
encoder-decoder
text2text-generation
Trained with AutoTrain
Instructions to use chiakya/codebert-gpt2-Summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chiakya/codebert-gpt2-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="chiakya/codebert-gpt2-Summarization")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("chiakya/codebert-gpt2-Summarization") model = AutoModelForSeq2SeqLM.from_pretrained("chiakya/codebert-gpt2-Summarization") - Notebooks
- Google Colab
- Kaggle
| { | |
| "bos_token_id": 50256, | |
| "decoder_start_token_id": 0, | |
| "early_stopping": true, | |
| "eos_token_id": 2, | |
| "length_penalty": 2.0, | |
| "max_length": 64, | |
| "min_length": 5, | |
| "no_repeat_ngram_size": 3, | |
| "num_beams": 4, | |
| "pad_token_id": 1, | |
| "transformers_version": "4.29.2" | |
| } | |