Instructions to use sravaniayyagari/lora_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use sravaniayyagari/lora_model with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("bitext/Mistral-7B-Mortgage-Loans") model = PeftModel.from_pretrained(base_model, "sravaniayyagari/lora_model") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from sravaniayyagari/lora_model: direct link, hf CLI and curl.
- Browser
- Download file 168 MB
-
https://huggingface.co/sravaniayyagari/lora_model/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://sravaniayyagari/lora_model/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/sravaniayyagari/lora_model/resolve/main/adapter_model.safetensors
168 MB
- Xet hash:
- d857ce24b5366142c273e0210f2783500d3139814d9f048aeb58edcf9b66e5a3
- Size of remote file:
- 168 MB
- SHA256:
- d8d5532b964b79b5b62aa59aa651d06fd36d8854629162083ce1b8ed71cebec1
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