Instructions to use Kaspar/bert_ecco_ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kaspar/bert_ecco_ft with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Kaspar/bert_ecco_ft")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Kaspar/bert_ecco_ft") model = AutoModelForMaskedLM.from_pretrained("Kaspar/bert_ecco_ft", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download added_tokens.json from Kaspar/bert_ecco_ft: direct link, hf CLI and curl.
- Browser
- Download file 22 Bytes
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https://huggingface.co/Kaspar/bert_ecco_ft/resolve/main/added_tokens.json
- Command line
-
hf download hf://Kaspar/bert_ecco_ft/added_tokens.json
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curl -L -o added_tokens.json https://huggingface.co/Kaspar/bert_ecco_ft/resolve/main/added_tokens.json
22 Bytes
| { | |
| "[TIME]": 30522 | |
| } | |