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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 274 Bytes
b2ab6e4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | {
"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"
}
|