Instructions to use robiulawaldev/a53d87dd-9d44-4aae-a2b8-3f1fc74920c3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use robiulawaldev/a53d87dd-9d44-4aae-a2b8-3f1fc74920c3 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-2-2b-it") model = PeftModel.from_pretrained(base_model, "robiulawaldev/a53d87dd-9d44-4aae-a2b8-3f1fc74920c3") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.model from robiulawaldev/a53d87dd-9d44-4aae-a2b8-3f1fc74920c3: direct link, hf CLI and curl.
- Browser
- Download file 4.24 MB
-
https://huggingface.co/robiulawaldev/a53d87dd-9d44-4aae-a2b8-3f1fc74920c3/resolve/main/tokenizer.model
- Command line
-
hf download hf://robiulawaldev/a53d87dd-9d44-4aae-a2b8-3f1fc74920c3/tokenizer.model
-
curl -L -o tokenizer.model https://huggingface.co/robiulawaldev/a53d87dd-9d44-4aae-a2b8-3f1fc74920c3/resolve/main/tokenizer.model
4.24 MB
- Xet hash:
- fde8653f2f656fb4ab30c2a5db64ba86a916a86134355b76c3bf26a5b022b323
- Size of remote file:
- 4.24 MB
- SHA256:
- 61a7b147390c64585d6c3543dd6fc636906c9af3865a5548f27f31aee1d4c8e2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.