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:
- 9c088a995ad314272337741266d60d1d58d6a7eac8050894cae7963404eee7d9
- Size of remote file:
- 1.97 GB
- SHA256:
- 514a9ab37066e8dda5fdd08341fccb5591fe3e683eb4cf1ed6f542e9ec7ccca8
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