Instructions to use cimol/bde87e4f-57eb-41e1-9fb6-fd915800591d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use cimol/bde87e4f-57eb-41e1-9fb6-fd915800591d with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("jingyeom/seal3.1.6n_7b") model = PeftModel.from_pretrained(base_model, "cimol/bde87e4f-57eb-41e1-9fb6-fd915800591d") - Notebooks
- Google Colab
- Kaggle
Download last-checkpoint/tokenizer.json from cimol/bde87e4f-57eb-41e1-9fb6-fd915800591d: direct link, hf CLI and curl.
- Browser
- Download file 4.8 MB
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https://huggingface.co/cimol/bde87e4f-57eb-41e1-9fb6-fd915800591d/resolve/main/last-checkpoint/tokenizer.json
- Command line
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hf download hf://cimol/bde87e4f-57eb-41e1-9fb6-fd915800591d/last-checkpoint/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/cimol/bde87e4f-57eb-41e1-9fb6-fd915800591d/resolve/main/last-checkpoint/tokenizer.json
4.8 MB
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