Instructions to use sraj/Merge_Drop_MARK_FastText with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sraj/Merge_Drop_MARK_FastText with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="sraj/Merge_Drop_MARK_FastText")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("sraj/Merge_Drop_MARK_FastText") model = AutoModelForMaskedLM.from_pretrained("sraj/Merge_Drop_MARK_FastText") - Notebooks
- Google Colab
- Kaggle
| models: | |
| - model: sraj/CMB_FWEdu_V2_FastTxt_CX_LRD | |
| parameters: | |
| weight: 1.0 | |
| - model: sraj/CMB_WX_SYN_CX_LRD | |
| parameters: | |
| weight: 1.0 | |
| # - model: sraj/CMB_SYN_QWEN35_122B_FP8_10K_SEED42_CX_LRD | |
| # parameters: | |
| # weight: 1.0 | |
| merge_method: linear | |
| parameters: | |
| normalize: true | |
| dtype: bfloat16 |