Instructions to use veneres/monobert-asnq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use veneres/monobert-asnq with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="veneres/monobert-asnq")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("veneres/monobert-asnq") model = AutoModelForSequenceClassification.from_pretrained("veneres/monobert-asnq", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from veneres/monobert-asnq: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/veneres/monobert-asnq/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://veneres/monobert-asnq/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/veneres/monobert-asnq/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 34ec4e7feec11e9297737482b9ffbcaabbd4c69ebc5437ef18a3ed81983f9efd
- Size of remote file:
- 438 MB
- SHA256:
- ef00f7ac869254a2104ef537a649439dd3019ecf3621267f2b67ddee7d0245be
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