Instructions to use JMLizano/FinRL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use JMLizano/FinRL with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/qwen3-4b-unsloth-bnb-4bit") model = PeftModel.from_pretrained(base_model, "JMLizano/FinRL") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from JMLizano/FinRL: direct link, hf CLI and curl.
- Browser
- Download file 537 MB
-
https://huggingface.co/JMLizano/FinRL/resolve/main/optimizer.pt
- Command line
-
hf download hf://JMLizano/FinRL/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/JMLizano/FinRL/resolve/main/optimizer.pt
537 MB
- Xet hash:
- 5135e93f0aa0863b7d44296bca6b09221527130fb7594b18db066decc094aa81
- Size of remote file:
- 537 MB
- SHA256:
- a140336c7b104ea7df8cbd8f98974b0637e05d7caf66ef43801f9b27c9bace69
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