Robotics
Transformers
Safetensors
mistral
text-generation
Merge
mergekit
lazymergekit
google-bert/bert-base-uncased
sentence-transformers/stsb-xlm-r-multilingual
text-generation-inference
Instructions to use nagayama0706/administrative_processing_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nagayama0706/administrative_processing_model with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("nagayama0706/administrative_processing_model") model = AutoModelForCausalLM.from_pretrained("nagayama0706/administrative_processing_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1e090c2d2774ea7875da72d682c12600bd69085e9c28674b917a49fe82ccffe2
- Size of remote file:
- 493 kB
- SHA256:
- dadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055
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