Instructions to use lauraha/esm_6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lauraha/esm_6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="lauraha/esm_6")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("lauraha/esm_6") model = AutoModelForMaskedLM.from_pretrained("lauraha/esm_6", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from lauraha/esm_6: direct link, hf CLI and curl.
- Browser
- Download file 5.18 kB
-
https://huggingface.co/lauraha/esm_6/resolve/main/training_args.bin
- Command line
-
hf download hf://lauraha/esm_6/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/lauraha/esm_6/resolve/main/training_args.bin
5.18 kB
- Xet hash:
- 0b7b41d9bbfec735f15a55980f009fb9f181686508f7807ad5d057ad6c092572
- Size of remote file:
- 5.18 kB
- SHA256:
- 4c4608d547015876e9a81ad3876e551b0e959b5f397fcb661c8723501bfb22de
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