Instructions to use juliensimon/imdb-demo-infinity with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use juliensimon/imdb-demo-infinity with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="juliensimon/imdb-demo-infinity")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("juliensimon/imdb-demo-infinity", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 361 Bytes
4156f8b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | import requests as r
import time
input_data = { "inputs": "Dune is something rarely seen anymore – it’s an epic."}
url = "http://localhost:8080/predict"
sum=0
for i in range(0,1000):
response = r.post(url, json=input_data)
resp_time = response.headers["x-compute-time"]
sum+=float(resp_time)
sum/=1000
print(f"{round(float(sum),6)*1000}ms")
|