Instructions to use howdi2000/may_v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use howdi2000/may_v3 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("beomi/llama-2-ko-7b") model = PeftModel.from_pretrained(base_model, "howdi2000/may_v3") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from howdi2000/may_v3: direct link, hf CLI and curl.
- Browser
- Download file 888 Bytes
-
https://huggingface.co/howdi2000/may_v3/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://howdi2000/may_v3/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/howdi2000/may_v3/resolve/main/pytorch_model.bin
888 Bytes
- Xet hash:
- 692c2fdfa4629052f89df52017e7ef336b01a57c58dd09e07b34b7aaca6ce269
- Size of remote file:
- 888 Bytes
- SHA256:
- 049c26b844b79121ddd8379f7f69194e63f6fbf6aa007eeac0c66f17eebb8893
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