Text Classification
Transformers
PyTorch
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use jambo/marker-associations-snp-binary-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jambo/marker-associations-snp-binary-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jambo/marker-associations-snp-binary-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jambo/marker-associations-snp-binary-base") model = AutoModelForSequenceClassification.from_pretrained("jambo/marker-associations-snp-binary-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from jambo/marker-associations-snp-binary-base: direct link, hf CLI and curl.
- Browser
- Download file 2.86 kB
-
https://huggingface.co/jambo/marker-associations-snp-binary-base/resolve/main/training_args.bin
- Command line
-
hf download hf://jambo/marker-associations-snp-binary-base/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/jambo/marker-associations-snp-binary-base/resolve/main/training_args.bin
2.86 kB
- Xet hash:
- 08761a546b1f99162c0cdcf97730a5e4bce65cc9766bac95debb633b264db382
- Size of remote file:
- 2.86 kB
- SHA256:
- 4a5492b5944ebce066a91a9bd8d70311c4cf0d722707ae7c8b202a0724e6f28b
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