Instructions to use hfl/rbt3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hfl/rbt3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hfl/rbt3")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hfl/rbt3") model = AutoModelForMaskedLM.from_pretrained("hfl/rbt3", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download added_tokens.json from hfl/rbt3: direct link, hf CLI and curl.
- Browser
- Download file 2 Bytes
-
https://huggingface.co/hfl/rbt3/resolve/main/added_tokens.json
- Command line
-
hf download hf://hfl/rbt3/added_tokens.json
-
curl -L -o added_tokens.json https://huggingface.co/hfl/rbt3/resolve/main/added_tokens.json
2 Bytes
| {} |