Instructions to use nepp1d0/prot_bert_classification_finetuned_karolina_es_20e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nepp1d0/prot_bert_classification_finetuned_karolina_es_20e with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nepp1d0/prot_bert_classification_finetuned_karolina_es_20e")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nepp1d0/prot_bert_classification_finetuned_karolina_es_20e") model = AutoModelForSequenceClassification.from_pretrained("nepp1d0/prot_bert_classification_finetuned_karolina_es_20e", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from nepp1d0/prot_bert_classification_finetuned_karolina_es_20e: direct link, hf CLI and curl.
- Browser
- Download file 3.38 kB
-
https://huggingface.co/nepp1d0/prot_bert_classification_finetuned_karolina_es_20e/resolve/main/training_args.bin
- Command line
-
hf download hf://nepp1d0/prot_bert_classification_finetuned_karolina_es_20e/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/nepp1d0/prot_bert_classification_finetuned_karolina_es_20e/resolve/main/training_args.bin
3.38 kB
- Xet hash:
- be0acdad94fa605aa704b7e0435a41ee131ad61c24cdb1bd0d45293cffa61a92
- Size of remote file:
- 3.38 kB
- SHA256:
- 0816f15549e75f75cbe6c9bb44a47eeb58c1f7dfcd06e77fd6eeee545e15573c
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