Instructions to use IIIT-L/muril-base-cased-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/muril-base-cased-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/muril-base-cased-finetuned-non-code-mixed-DS")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("IIIT-L/muril-base-cased-finetuned-non-code-mixed-DS") model = AutoModelForSequenceClassification.from_pretrained("IIIT-L/muril-base-cased-finetuned-non-code-mixed-DS", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from IIIT-L/muril-base-cased-finetuned-non-code-mixed-DS: direct link, hf CLI and curl.
- Browser
- Download file 950 MB
-
https://huggingface.co/IIIT-L/muril-base-cased-finetuned-non-code-mixed-DS/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://IIIT-L/muril-base-cased-finetuned-non-code-mixed-DS/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/IIIT-L/muril-base-cased-finetuned-non-code-mixed-DS/resolve/main/pytorch_model.bin
950 MB
- Xet hash:
- 50622d967ebcd864c1e2a0b824387ce67acd5344c192a7beab9e0146b061594b
- Size of remote file:
- 950 MB
- SHA256:
- c2bd55f846ced74aa26252dbd272ebeff46cab6740444c08d1be31636cdf4748
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