Instructions to use Bugpie/dummy-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Bugpie/dummy-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Bugpie/dummy-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Bugpie/dummy-model") model = AutoModelForMaskedLM.from_pretrained("Bugpie/dummy-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model
Verified signatureThis is an automated PR created with https://huggingface.co/spaces/safetensors/convert This new file is equivalent to `pytorch_model.bin` but safe in the sense that no arbitrary code can be put into it. These files also happen to load much faster than their pytorch counterpart: https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb The widgets on your model page will run using this model even if this is not merged making sure the file actually works. If you find any issues: please report here: https://huggingface.co/spaces/safetensors/convert/discussions Feel free to ignore this PR.a50501b
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--- language: en tags: - exbert license: apache-2.0 datasets: - bookcorpus - wikipedia --- ## Model description ## Intended uses & limitations ## How to use ## Limitations and bias ## Training data ## Training procedure ## Evaluation results484555c -
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--- language: en tags: - exbert license: apache-2.0 datasets: - bookcorpus - wikipedia --- ## Model description ## Intended uses & limitations ## How to use ## Limitations and bias ## Training data ## Training procedure ## Evaluation results8c15507 -
--- language: en tags: - exbert license: apache-2.0 datasets: - bookcorpus - wikipedia --- ## Model description ## Intended uses & limitations ## How to use ## Limitations and bias ## Training data ## Training procedure ## Evaluation results
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##Model description ##Intended uses & limitations ##How to use ##Limitations and bias ##Training data ##Training procedure ##Evaluation results2e8583c
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