Instructions to use tjayant/bloom-560m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tjayant/bloom-560m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tjayant/bloom-560m")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tjayant/bloom-560m") model = AutoModelForSequenceClassification.from_pretrained("tjayant/bloom-560m", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from tjayant/bloom-560m: direct link, hf CLI and curl.
- Browser
- Download file 14.5 MB
-
https://huggingface.co/tjayant/bloom-560m/resolve/refs%2Fpr%2F1/tokenizer.json
- Command line
-
hf download hf://tjayant/bloom-560m@refs/pr/1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/tjayant/bloom-560m/resolve/refs%2Fpr%2F1/tokenizer.json
14.5 MB
- Xet hash:
- f30570a0444192028de719f24e40248b41a2a9232b8dfd8558d1944b0da1641b
- Size of remote file:
- 14.5 MB
- SHA256:
- ddccca19e6cee347f93af7c3743c679a1556d7dfa6e0f60f8b320acdf7d6f446
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