Instructions to use karthik19967829/XLM-R-en-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karthik19967829/XLM-R-en-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="karthik19967829/XLM-R-en-model", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("karthik19967829/XLM-R-en-model") model = AutoModelForTokenClassification.from_pretrained("karthik19967829/XLM-R-en-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ba2064aabe00a329c403f52af7379f44b3214efa089658740cbadf0c73e5e349
- Size of remote file:
- 2.93 kB
- SHA256:
- e6fad71acfc96adb09cd27402d170a374d5d3cab6d661ab4b8ebcd392d45b44d
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