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 pytorch_model.bin from nepp1d0/prot_bert_classification_finetuned_karolina_es_20e: direct link, hf CLI and curl.
- Browser
- Download file 1.68 GB
-
https://huggingface.co/nepp1d0/prot_bert_classification_finetuned_karolina_es_20e/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://nepp1d0/prot_bert_classification_finetuned_karolina_es_20e/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/nepp1d0/prot_bert_classification_finetuned_karolina_es_20e/resolve/main/pytorch_model.bin
1.68 GB
- Xet hash:
- 24155a56ab6a5db345ef12269595c27b92b25fa3958a5d641c7a122b9860c2a6
- Size of remote file:
- 1.68 GB
- SHA256:
- 76b7e7addab33a33fb6ac15dfaad85de389243b6f73ec137bbf479f0a6760a12
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