File size: 1,610 Bytes
0d74ced 5cd8b35 24646b8 5cd8b35 6c23536 5cd8b35 0d74ced |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 |
---
tags:
- autotrain
- summarization
language:
- unk
widget:
- text: "I love AutoTrain"
datasets:
- sudeepshouche/autotrain-data-sushi
co2_eq_emissions:
emissions: 4.535146076696761
---
# Model Trained Using AutoTrain
- Problem type: Summarization
- Model ID: 94046145981
- CO2 Emissions (in grams): 4.5351
## Validation Metrics
- Loss: 1.876
- Rouge1: 45.886
- Rouge2: 18.852
- RougeL: 27.850
- RougeLsum: 40.554
- Gen Len: 104.307
## 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/sudeepshouche/autotrain-sushi-94046145981
```
Or try this python code:
```python
class TextSummarizer:
def __init__(self):
self.api_token = <HF_TOKEN>
self.model = "sudeepshouche/autotrain-sushi-94046145981"
def summarize(self, content):
api_url = f"https://api-inference.huggingface.co/models/{self.model}"
headers = {"Authorization": f"Bearer {self.api_token}"}
payload = {"inputs": content}
try:
response = requests.post(api_url, headers=headers, json=payload)
response.raise_for_status()
return response.json()
except requests.RequestException as e:
print(f"Error during summarization: {e}")
# logging.error(f"Error during summarization: {e}")
return [{'summary_text': content}]
content = <CONTENT_TO_SUMMARIZE>
output = TextSummarizer().summarize(content)
print (output[0]["summary_text"] )
``` |