Instructions to use shibajustfor/b0a2a05e-23f0-4fa7-97d5-312eb1c52a0e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use shibajustfor/b0a2a05e-23f0-4fa7-97d5-312eb1c52a0e with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/workspace/input_data/NousResearch/Meta-Llama-3-8B-Alternate-Tokenizer") model = PeftModel.from_pretrained(base_model, "shibajustfor/b0a2a05e-23f0-4fa7-97d5-312eb1c52a0e") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 16dbebbf87ec3b264caffa5aae1208c11f26ab9e8b90e5906da24d576c712186
- Size of remote file:
- 17.2 MB
- SHA256:
- 06848e95e34be87e26934cd584d8a7e85433a81f94231c66c2cf780c8dc05eab
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