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
Download code/predict.py from juliensimon/imdb-demo-infinity: direct link, hf CLI and curl.
- Browser
- Download file 368 Bytes
-
https://huggingface.co/juliensimon/imdb-demo-infinity/resolve/main/code/predict.py
- Command line
-
hf download hf://juliensimon/imdb-demo-infinity/code/predict.py
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curl -L -o predict.py https://huggingface.co/juliensimon/imdb-demo-infinity/resolve/main/code/predict.py
368 Bytes
| import time | |
| from transformers import pipeline | |
| pipeline = pipeline("sentiment-analysis", model="juliensimon/autonlp-imdb-demo-hf-16622767", use_auth_token=True) | |
| data = "Dune is something rarely seen anymore – it’s an epic." | |
| tick=time.time_ns() | |
| for i in range(0,100): | |
| response=pipeline(data) | |
| tock=time.time_ns() | |
| print("%.2fms" % ((tock-tick)/1000/1000/100)) | |