Instructions to use PoetschLab/GROVER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PoetschLab/GROVER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="PoetschLab/GROVER")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("PoetschLab/GROVER") model = AutoModelForMaskedLM.from_pretrained("PoetschLab/GROVER", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download tokenized_chromosomes/chr_4_mapper.pkl from PoetschLab/GROVER: direct link, hf CLI and curl.
- Browser
- Download file 956 MB
-
https://huggingface.co/PoetschLab/GROVER/resolve/main/tokenized_chromosomes/chr_4_mapper.pkl
- Command line
-
hf download hf://PoetschLab/GROVER/tokenized_chromosomes/chr_4_mapper.pkl
-
curl -L -o chr_4_mapper.pkl https://huggingface.co/PoetschLab/GROVER/resolve/main/tokenized_chromosomes/chr_4_mapper.pkl
956 MB
- Xet hash:
- d8b65500de153a460aa60415f3c12948152edf81896688c63d776d286cebe293
- Size of remote file:
- 956 MB
- SHA256:
- eb0898c25964219c4ad0226b9f6924fc903a799c303dc751d6dee513bc975933
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