Instructions to use asahi417/tner-roberta-large-tweet-st with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use asahi417/tner-roberta-large-tweet-st with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="asahi417/tner-roberta-large-tweet-st")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("asahi417/tner-roberta-large-tweet-st") model = AutoModelForTokenClassification.from_pretrained("asahi417/tner-roberta-large-tweet-st", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from asahi417/tner-roberta-large-tweet-st: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/asahi417/tner-roberta-large-tweet-st/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://asahi417/tner-roberta-large-tweet-st/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/asahi417/tner-roberta-large-tweet-st/resolve/main/pytorch_model.bin
1.42 GB
- Xet hash:
- 11b04002870f445975ebc097141441b7b25296897074703cbc85493bc1cbb7e5
- Size of remote file:
- 1.42 GB
- SHA256:
- 538f891d497581baf96a239a8f2ef35351e411d9d6ecc14e76f4eb941f6c34df
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