Instructions to use fakespot-ai/roberta-base-ai-text-detection-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fakespot-ai/roberta-base-ai-text-detection-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="fakespot-ai/roberta-base-ai-text-detection-v1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("fakespot-ai/roberta-base-ai-text-detection-v1") model = AutoModelForSequenceClassification.from_pretrained("fakespot-ai/roberta-base-ai-text-detection-v1", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from fakespot-ai/roberta-base-ai-text-detection-v1: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/fakespot-ai/roberta-base-ai-text-detection-v1/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://fakespot-ai/roberta-base-ai-text-detection-v1/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/fakespot-ai/roberta-base-ai-text-detection-v1/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- ecc5a5e1b9a4d78006bd268051617cb5e5713975fe0a3a6589ff89c196609b5e
- Size of remote file:
- 499 MB
- SHA256:
- e8624aaf898074697c13a698ddcfe404a2b5fa5f275f6412343f2b0f946e4b7d
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