Instructions to use wolfram/miquliz-120b-v2.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wolfram/miquliz-120b-v2.0 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("wolfram/miquliz-120b-v2.0", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| merge_method: linear | |
| parameters: | |
| weight: 1.0 | |
| slices: | |
| - sources: | |
| - model: 152334H/miqu-1-70b-sf | |
| layer_range: [0, 1] | |
| - model: lizpreciatior/lzlv_70b_fp16_hf | |
| layer_range: [0, 1] | |
| parameters: | |
| weight: 0 | |
| - sources: | |
| - model: 152334H/miqu-1-70b-sf | |
| layer_range: [1, 20] | |
| - sources: | |
| - model: lizpreciatior/lzlv_70b_fp16_hf | |
| layer_range: [10, 30] | |
| - sources: | |
| - model: 152334H/miqu-1-70b-sf | |
| layer_range: [20, 40] | |
| - sources: | |
| - model: lizpreciatior/lzlv_70b_fp16_hf | |
| layer_range: [30, 50] | |
| - sources: | |
| - model: 152334H/miqu-1-70b-sf | |
| layer_range: [40, 60] | |
| - sources: | |
| - model: lizpreciatior/lzlv_70b_fp16_hf | |
| layer_range: [50, 70] | |
| - sources: | |
| - model: 152334H/miqu-1-70b-sf | |
| layer_range: [60, 79] | |
| - sources: | |
| - model: 152334H/miqu-1-70b-sf | |
| layer_range: [79, 80] | |
| - model: lizpreciatior/lzlv_70b_fp16_hf | |
| layer_range: [79, 80] | |
| parameters: | |
| weight: 0 | |
| dtype: float16 | |
| tokenizer_source: model:152334H/miqu-1-70b-sf | |