Instructions to use deepaknh/falcon7b-FineTuningQLORA_FullTrainDataset with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use deepaknh/falcon7b-FineTuningQLORA_FullTrainDataset with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("ybelkada/falcon-7b-sharded-bf16") model = PeftModel.from_pretrained(base_model, "deepaknh/falcon7b-FineTuningQLORA_FullTrainDataset") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from deepaknh/falcon7b-FineTuningQLORA_FullTrainDataset: direct link, hf CLI and curl.
- Browser
- Download file 131 MB
-
https://huggingface.co/deepaknh/falcon7b-FineTuningQLORA_FullTrainDataset/resolve/main/adapter_model.bin
- Command line
-
hf download hf://deepaknh/falcon7b-FineTuningQLORA_FullTrainDataset/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/deepaknh/falcon7b-FineTuningQLORA_FullTrainDataset/resolve/main/adapter_model.bin
131 MB
- Xet hash:
- 7222d2e6885de287e988bd369757dab4e63491840f13fab449b4b1e1447369b0
- Size of remote file:
- 131 MB
- SHA256:
- 23c4d21b7ceb9f8a82c008778fdd5f2aa7c3d7a5a16bed72bf9f9ee401c7a53e
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