Instructions to use MetR-Metapercept/llama2-dita-analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use MetR-Metapercept/llama2-dita-analysis with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Llama-2-7b-chat-hf") model = PeftModel.from_pretrained(base_model, "MetR-Metapercept/llama2-dita-analysis") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from MetR-Metapercept/llama2-dita-analysis: direct link, hf CLI and curl.
- Browser
- Download file 134 MB
-
https://huggingface.co/MetR-Metapercept/llama2-dita-analysis/resolve/main/adapter_model.bin
- Command line
-
hf download hf://MetR-Metapercept/llama2-dita-analysis/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/MetR-Metapercept/llama2-dita-analysis/resolve/main/adapter_model.bin
134 MB
- Xet hash:
- f5769399f343a3f0dd238824a8304f03e82923c78b2bad5a869ea243f6880a15
- Size of remote file:
- 134 MB
- SHA256:
- b3d1dbc71f5febb8b1e053618c827a1cba4af90afdf392805ccbddb0adf79945
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