Instructions to use tanganke/flan-t5-base_glue-rte_lora-16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use tanganke/flan-t5-base_glue-rte_lora-16 with PEFT:
from peft import PeftModel from transformers import AutoModelForSeq2SeqLM base_model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-base") model = PeftModel.from_pretrained(base_model, "tanganke/flan-t5-base_glue-rte_lora-16") - Notebooks
- Google Colab
- Kaggle
Download adapter_config.json from tanganke/flan-t5-base_glue-rte_lora-16: direct link, hf CLI and curl.
- Browser
- Download file 637 Bytes
-
https://huggingface.co/tanganke/flan-t5-base_glue-rte_lora-16/resolve/main/adapter_config.json
- Command line
-
hf download hf://tanganke/flan-t5-base_glue-rte_lora-16/adapter_config.json
-
curl -L -o adapter_config.json https://huggingface.co/tanganke/flan-t5-base_glue-rte_lora-16/resolve/main/adapter_config.json
637 Bytes
| { | |
| "alpha_pattern": {}, | |
| "auto_mapping": null, | |
| "base_model_name_or_path": "google/flan-t5-base", | |
| "bias": "none", | |
| "fan_in_fan_out": false, | |
| "inference_mode": true, | |
| "init_lora_weights": true, | |
| "layer_replication": null, | |
| "layers_pattern": null, | |
| "layers_to_transform": null, | |
| "loftq_config": {}, | |
| "lora_alpha": 32, | |
| "lora_dropout": 0.1, | |
| "megatron_config": null, | |
| "megatron_core": "megatron.core", | |
| "modules_to_save": null, | |
| "peft_type": "LORA", | |
| "r": 16, | |
| "rank_pattern": {}, | |
| "revision": null, | |
| "target_modules": [ | |
| "q", | |
| "v" | |
| ], | |
| "task_type": "SEQ_2_SEQ_LM", | |
| "use_dora": false, | |
| "use_rslora": false | |
| } |