Instructions to use asahi417/tner-roberta-base-tweet-2020 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use asahi417/tner-roberta-base-tweet-2020 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="asahi417/tner-roberta-base-tweet-2020")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("asahi417/tner-roberta-base-tweet-2020") model = AutoModelForTokenClassification.from_pretrained("asahi417/tner-roberta-base-tweet-2020", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from asahi417/tner-roberta-base-tweet-2020: direct link, hf CLI and curl.
- Browser
- Download file 496 MB
-
https://huggingface.co/asahi417/tner-roberta-base-tweet-2020/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://asahi417/tner-roberta-base-tweet-2020/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/asahi417/tner-roberta-base-tweet-2020/resolve/main/pytorch_model.bin
496 MB
- Xet hash:
- 514c146b81d01a5e778f5b550b7376736fd6c5a0eb1bafcbf2760f8212c58a57
- Size of remote file:
- 496 MB
- SHA256:
- 44506e280789f0ec629c4e1dfd77219f1ce44b7da2cd243978b28f55239fed90
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