Instructions to use beast33/38d28935-f58b-4d42-9ecd-9aac981f2592 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use beast33/38d28935-f58b-4d42-9ecd-9aac981f2592 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-7b-it") model = PeftModel.from_pretrained(base_model, "beast33/38d28935-f58b-4d42-9ecd-9aac981f2592") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from beast33/38d28935-f58b-4d42-9ecd-9aac981f2592: direct link, hf CLI and curl.
- Browser
- Download file 34.4 MB
-
https://huggingface.co/beast33/38d28935-f58b-4d42-9ecd-9aac981f2592/resolve/main/tokenizer.json
- Command line
-
hf download hf://beast33/38d28935-f58b-4d42-9ecd-9aac981f2592/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/beast33/38d28935-f58b-4d42-9ecd-9aac981f2592/resolve/main/tokenizer.json
34.4 MB
- Xet hash:
- 922b7ca7ba4d2f66d92f0b1191fe3a4010a67fe8265e9c69b1d65f60f9970339
- Size of remote file:
- 34.4 MB
- SHA256:
- f559f2189f392b4555613965f089e7c4d300b41fbe080bf79da0d676e33ee7f0
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