Instructions to use Recognai/zeroshot_selectra_small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Recognai/zeroshot_selectra_small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="Recognai/zeroshot_selectra_small")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Recognai/zeroshot_selectra_small") model = AutoModelForSequenceClassification.from_pretrained("Recognai/zeroshot_selectra_small") - Notebooks
- Google Colab
- Kaggle
Running this model on old cpus?
#2
by iagovar - opened
Hi! I have a hobby project (https://cometocoruna.com) where I scrape a lot of events, and I need to clasify what type of events they are.
I find this model good enough for my purposes, but I have a problem:
I'm going lean as I currently have no job currently, so I don't want to spend money on running this.
My server is an atom CPU + 4 GB Ram and no AVX sitting in my bedroom.
I don't think I will be able to use the free-tier API as I will make lots of inferences.
Do you think such model is viable to run in my hardware? The compute time in HF is fast but they run it in Xeons.
iagovar changed discussion status to closed
iagovar changed discussion status to open