Instructions to use tner/roberta-large-tweetner7-2021 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tner/roberta-large-tweetner7-2021 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="tner/roberta-large-tweetner7-2021")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("tner/roberta-large-tweetner7-2021") model = AutoModelForTokenClassification.from_pretrained("tner/roberta-large-tweetner7-2021", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from tner/roberta-large-tweetner7-2021: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/tner/roberta-large-tweetner7-2021/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://tner/roberta-large-tweetner7-2021/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/tner/roberta-large-tweetner7-2021/resolve/main/pytorch_model.bin
1.42 GB
- Xet hash:
- ab1117d0c7f487468bbb7871d2956a938e5a15caf38a3e47e99ae47a40c8a5df
- Size of remote file:
- 1.42 GB
- SHA256:
- c67bd28f55ab17b52414188ee5ef78a13f9d50a5aa78ae53d0df22c9a5839412
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