Question Answering
Transformers
Safetensors
mistral
text-generation
Merge
mergekit
lazymergekit
huggingface/CodeBERTa-language-id
Sharathhebbar24/code_gpt2
text-generation-inference
Instructions to use nagayama0706/coding_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nagayama0706/coding_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="nagayama0706/coding_model")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("nagayama0706/coding_model") model = AutoModelForMultimodalLM.from_pretrained("nagayama0706/coding_model") - 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 | |