Instructions to use jayzeng/llm-fun with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use jayzeng/llm-fun with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen1.5-MoE-A2.7B") model = PeftModel.from_pretrained(base_model, "jayzeng/llm-fun") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-1900/optimizer.pt from jayzeng/llm-fun: direct link, hf CLI and curl.
- Browser
- Download file 1.04 GB
-
https://huggingface.co/jayzeng/llm-fun/resolve/main/checkpoint-1900/optimizer.pt
- Command line
-
hf download hf://jayzeng/llm-fun/checkpoint-1900/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/jayzeng/llm-fun/resolve/main/checkpoint-1900/optimizer.pt
1.04 GB
- Xet hash:
- d2ddd868c873d65ef07be5a27df87a796a0f2578a033a7c876de5d40cc425c3c
- Size of remote file:
- 1.04 GB
- SHA256:
- d722de2017d50000f2c35fa44be3c6d1084dd81ee4c129572520a1822ed98bcd
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