Token Classification
Transformers
Safetensors
English
esm
protein language model
protein sequence annotation
Instructions to use ProteinSequenceAnnotation/PSALM-1-clan with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProteinSequenceAnnotation/PSALM-1-clan with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ProteinSequenceAnnotation/PSALM-1-clan")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ProteinSequenceAnnotation/PSALM-1-clan", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from ProteinSequenceAnnotation/PSALM-1-clan: direct link, hf CLI and curl.
- Browser
- Download file 708 Bytes
-
https://huggingface.co/ProteinSequenceAnnotation/PSALM-1-clan/resolve/main/README.md
- Command line
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hf download hf://ProteinSequenceAnnotation/PSALM-1-clan/README.md
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curl -L -o README.md https://huggingface.co/ProteinSequenceAnnotation/PSALM-1-clan/resolve/main/README.md
708 Bytes
metadata
tags:
- esm
- protein language model
- protein sequence annotation
license: cc-by-4.0
language:
- en
pipeline_tag: token-classification
Model Card for Model ID
NOTE: PSALM-1 has not been trained on all Pfam families, as it has been trained and benchmarked on highly-curated datasets with strict sequence similarity guarantees between train and test data. PSALM-1b (trained on all families in Pfam 35.0) is coming soon
PSALM-1-clan is a 69M parameter model that takes as input ESM-2 residue-level protein sequence emebeddings (unpooled) and outputs a distribution over Pfam domain clans for each amino acid in the sequence. PSALM-1-clan uses a BiLSTM followed by a stack of dense layers