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
| slices: | |
| - sources: | |
| - model: OpenPipe/mistral-ft-optimized-1218 | |
| layer_range: [0, 32] | |
| - model: mlabonne/NeuralHermes-2.5-Mistral-7B | |
| layer_range: [0, 32] | |
| merge_method: slerp | |
| base_model: OpenPipe/mistral-ft-optimized-1218 | |
| parameters: | |
| t: | |
| - filter: self_attn | |
| value: [0, 0.5, 0.3, 0.7, 1] | |
| - filter: mlp | |
| value: [1, 0.5, 0.7, 0.3, 0] | |
| - value: 0.5 | |
| dtype: bfloat16 | |