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")# pip install -U transformers accelerate # 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
Download tokenizer_config.json from ScriptEdgeAI/MarathiSentiment-Bloom-560m: direct link, hf CLI and curl.
- Browser
- Download file 268 Bytes
-
https://huggingface.co/ScriptEdgeAI/MarathiSentiment-Bloom-560m/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://ScriptEdgeAI/MarathiSentiment-Bloom-560m/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/ScriptEdgeAI/MarathiSentiment-Bloom-560m/resolve/main/tokenizer_config.json
268 Bytes
| { | |
| "add_prefix_space": false, | |
| "bos_token": "<s>", | |
| "eos_token": "</s>", | |
| "name_or_path": "bigscience/bloom-560m", | |
| "pad_token": "<pad>", | |
| "padding_side": "left", | |
| "special_tokens_map_file": null, | |
| "tokenizer_class": "BloomTokenizer", | |
| "unk_token": "<unk>" | |
| } | |