Instructions to use tner/roberta-large-tweetner7-selflabel2020-continuous with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tner/roberta-large-tweetner7-selflabel2020-continuous with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="tner/roberta-large-tweetner7-selflabel2020-continuous")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("tner/roberta-large-tweetner7-selflabel2020-continuous") model = AutoModelForTokenClassification.from_pretrained("tner/roberta-large-tweetner7-selflabel2020-continuous", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from tner/roberta-large-tweetner7-selflabel2020-continuous: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/tner/roberta-large-tweetner7-selflabel2020-continuous/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://tner/roberta-large-tweetner7-selflabel2020-continuous/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/tner/roberta-large-tweetner7-selflabel2020-continuous/resolve/main/pytorch_model.bin
1.42 GB
- Xet hash:
- c7f666f5a4db3cbd9a4b2b28a921363027909273b22011e52c6dd9221f3db20d
- Size of remote file:
- 1.42 GB
- SHA256:
- a58d62bc66ef16ed250c1ea71e9b83ce1b71db8fb0aa926632add489dd1c62ec
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