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:
- 221a61df2e5716dc24cc44391926347b18449bbea3706e7768c9e50bb21a0659
- Size of remote file:
- 1.98 GB
- SHA256:
- f18e8eac94ce9582783c75b85a6b51d6c860e56eab65505d90d3894160e7c459
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