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: 699 Bytes
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tags:
- autotrain
- summarization
language:
- unk
widget:
- text: "I love AutoTrain"
datasets:
- chiakya/autotrain-data-gpt2
co2_eq_emissions:
emissions: 60.846249800297436
---
# Model Trained Using AutoTrain
- Problem type: Summarization
- Model ID: 99861147494
- CO2 Emissions (in grams): 60.8462
## Validation Metrics
- Loss: 1.003
- Rouge1: 0.100
- Rouge2: 0.000
- RougeL: 0.100
- RougeLsum: 0.100
- Gen Len: 38.316
## Usage
You can use cURL to access this model:
```
$ curl -X POST -H "Authorization: Bearer YOUR_HUGGINGFACE_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I love AutoTrain"}' https://api-inference.huggingface.co/chiakya/autotrain-gpt2-99861147494
``` |