Instructions to use monsterapi/llama2_SQL_Answers_finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use monsterapi/llama2_SQL_Answers_finetuned with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-7b-hf") model = PeftModel.from_pretrained(base_model, "monsterapi/llama2_SQL_Answers_finetuned") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from monsterapi/llama2_SQL_Answers_finetuned: direct link, hf CLI and curl.
- Browser
- Download file 33.6 MB
-
https://huggingface.co/monsterapi/llama2_SQL_Answers_finetuned/resolve/main/adapter_model.bin
- Command line
-
hf download hf://monsterapi/llama2_SQL_Answers_finetuned/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/monsterapi/llama2_SQL_Answers_finetuned/resolve/main/adapter_model.bin
33.6 MB
- Xet hash:
- e34f45bbbcd8449e5889c1bcb955c677aadc0183d0e855df009f1fea2d95c295
- Size of remote file:
- 33.6 MB
- SHA256:
- d676f5e81b579c3a68bf5c7611e5433a893a00686568a7009c996bba7f679373
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