Instructions to use ngocquangt2k46/90d10116-9f09-4362-b32c-19aeff53de18 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ngocquangt2k46/90d10116-9f09-4362-b32c-19aeff53de18 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Yarn-Llama-2-7b-64k") model = PeftModel.from_pretrained(base_model, "ngocquangt2k46/90d10116-9f09-4362-b32c-19aeff53de18") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/trainer_state.json from ngocquangt2k46/90d10116-9f09-4362-b32c-19aeff53de18: direct link, hf CLI and curl.
- Browser
- Download file 3.2 kB
-
https://huggingface.co/ngocquangt2k46/90d10116-9f09-4362-b32c-19aeff53de18/resolve/main/last-checkpoint/trainer_state.json
- Command line
-
hf download hf://ngocquangt2k46/90d10116-9f09-4362-b32c-19aeff53de18/last-checkpoint/trainer_state.json
-
curl -L -o trainer_state.json https://huggingface.co/ngocquangt2k46/90d10116-9f09-4362-b32c-19aeff53de18/resolve/main/last-checkpoint/trainer_state.json
3.2 kB
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