Instructions to use amkorba/mlm-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amkorba/mlm-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="amkorba/mlm-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("amkorba/mlm-model") model = AutoModelForMaskedLM.from_pretrained("amkorba/mlm-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from amkorba/mlm-model: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/amkorba/mlm-model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://amkorba/mlm-model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/amkorba/mlm-model/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- aa27ff226fbecad1e4fb54565af6d37d6ee4897e2fb94cfb3a2f90138258ee82
- Size of remote file:
- 268 MB
- SHA256:
- 8b2f89473c36ab29824ba103cad17dd2cc80e50de35d9d3a4f24dc1a0c872b2c
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