Instructions to use ScriptEdgeAI/MarathiSentiment-Bloom-560m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ScriptEdgeAI/MarathiSentiment-Bloom-560m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ScriptEdgeAI/MarathiSentiment-Bloom-560m")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ScriptEdgeAI/MarathiSentiment-Bloom-560m") model = AutoModelForSequenceClassification.from_pretrained("ScriptEdgeAI/MarathiSentiment-Bloom-560m", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from ScriptEdgeAI/MarathiSentiment-Bloom-560m: direct link, hf CLI and curl.
- Browser
- Download file 1.01 kB
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https://huggingface.co/ScriptEdgeAI/MarathiSentiment-Bloom-560m/resolve/cba653950a582cd460d57f9ae5fa6f80ccd57d4a/README.md
- Command line
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hf download hf://ScriptEdgeAI/MarathiSentiment-Bloom-560m@cba653950a582cd460d57f9ae5fa6f80ccd57d4a/README.md
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curl -L -o README.md https://huggingface.co/ScriptEdgeAI/MarathiSentiment-Bloom-560m/resolve/cba653950a582cd460d57f9ae5fa6f80ccd57d4a/README.md
1.01 kB
| language: | |
| - mr | |
| tags: | |
| - mr | |
| - sentiment | |
| - AutoTrain Compatible | |
| license: cc-by-nc-4.0 | |
| widget: | |
| - text: "मला तुम्ही आवडता.</s></s> मी तुझ्यावर प्रेम करतो." | |
| # Marathi-Bloom-560m is a Bloom fine-tuned model trained by ScriptEdge on MahaNLP tweets dataset from L3Cube-MahaNLP. | |
| ## Worked on by: | |
| Trained by: | |
| - Venkatesh Soni. | |
| Assistance: | |
| - Rayansh Srivastava. | |
| Supervision: | |
| - Akshay Ugale, Madhukar Alhat. | |
| ## Usage - | |
| - It is intended for non-commercial usages. | |
| ## Model best metrics | |
| | Data | Accuracy | | |
| |-------------------|---------------------| | |
| | Validation | 76.0 | | |
| | **Test** | **77.0** | | |
| Citation to L3CubePune by the dataset usage. | |
| ``` | |
| @article {joshi2022l3cube, | |
| title= {L3Cube-MahaNLP: Marathi Natural Language Processing Datasets, Models, and Library}, | |
| author= {Joshi, Raviraj}, | |
| journal= {arXiv preprint arXiv:2205.14728}, | |
| year= {2022} | |
| } | |
| ``` |