Instructions to use yevhenkost/cutiesRun28-05-2020-roberta-base-evidenceAlignment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yevhenkost/cutiesRun28-05-2020-roberta-base-evidenceAlignment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yevhenkost/cutiesRun28-05-2020-roberta-base-evidenceAlignment")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("yevhenkost/cutiesRun28-05-2020-roberta-base-evidenceAlignment") model = AutoModelForSequenceClassification.from_pretrained("yevhenkost/cutiesRun28-05-2020-roberta-base-evidenceAlignment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from yevhenkost/cutiesRun28-05-2020-roberta-base-evidenceAlignment: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/yevhenkost/cutiesRun28-05-2020-roberta-base-evidenceAlignment/resolve/main/model.safetensors
- Command line
-
hf download hf://yevhenkost/cutiesRun28-05-2020-roberta-base-evidenceAlignment/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/yevhenkost/cutiesRun28-05-2020-roberta-base-evidenceAlignment/resolve/main/model.safetensors
499 MB
- Xet hash:
- dd505f96d4c9b3280ba63213691f5a5e36a22ec28f441d0960f479b2ba70d47d
- Size of remote file:
- 499 MB
- SHA256:
- b1044c1fc529eca9d773d0be7b0dc41c4b024ef0b15c172f4c26a0402fcf8d92
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.