Instructions to use IIIT-L/roberta-large-finetuned-non-code-mixed-DS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IIIT-L/roberta-large-finetuned-non-code-mixed-DS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="IIIT-L/roberta-large-finetuned-non-code-mixed-DS")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("IIIT-L/roberta-large-finetuned-non-code-mixed-DS") model = AutoModelForSequenceClassification.from_pretrained("IIIT-L/roberta-large-finetuned-non-code-mixed-DS", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from IIIT-L/roberta-large-finetuned-non-code-mixed-DS: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/IIIT-L/roberta-large-finetuned-non-code-mixed-DS/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://IIIT-L/roberta-large-finetuned-non-code-mixed-DS/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/IIIT-L/roberta-large-finetuned-non-code-mixed-DS/resolve/main/pytorch_model.bin
1.42 GB
- Xet hash:
- 9d4bbd310ed58548e85a45a5a5b13a5e7aeda5a1905d3172de0fb31632fe6224
- Size of remote file:
- 1.42 GB
- SHA256:
- 0988c4695b727e4790241ee7d9de1e3b294c1dfe6d135cb32c50800e3f5cc0e2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.