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
| base_model: | |
| - sraj/CMB_WX_SYN_CX_LRD | |
| - sraj/CMB_FWEdu_V2_FastTxt_CX_LRD | |
| library_name: transformers | |
| tags: | |
| - mergekit | |
| - merge | |
| # merge_drop_MARK | |
| This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit). | |
| ## Merge Details | |
| ### Merge Method | |
| This model was merged using the [Linear](https://arxiv.org/abs/2203.05482) merge method. | |
| ### Models Merged | |
| The following models were included in the merge: | |
| * [sraj/CMB_WX_SYN_CX_LRD](https://huggingface.co/sraj/CMB_WX_SYN_CX_LRD) | |
| * [sraj/CMB_FWEdu_V2_FastTxt_CX_LRD](https://huggingface.co/sraj/CMB_FWEdu_V2_FastTxt_CX_LRD) | |
| ### Configuration | |
| The following YAML configuration was used to produce this model: | |
| ```yaml | |
| 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 | |
| ``` | |