Instructions to use seyonec/checkpoint-50000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use seyonec/checkpoint-50000 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="seyonec/checkpoint-50000")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("seyonec/checkpoint-50000") model = AutoModelForMaskedLM.from_pretrained("seyonec/checkpoint-50000", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from seyonec/checkpoint-50000: direct link, hf CLI and curl.
- Browser
- Download file 334 MB
-
https://huggingface.co/seyonec/checkpoint-50000/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://seyonec/checkpoint-50000/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/seyonec/checkpoint-50000/resolve/main/flax_model.msgpack
334 MB
- Xet hash:
- 2781320776c00dd3db1e79f22ae5a18f2c73ae0d33f9277cb20e7c3ac959bf78
- Size of remote file:
- 334 MB
- SHA256:
- bc9c9ab01d85873b6eb0a92ec07f4830c599188fba1afa95ab9bcbb5958ae370
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