Instructions to use serbanstein/invoiceextractor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use serbanstein/invoiceextractor with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("yahma/llama-7b-hf") model = PeftModel.from_pretrained(base_model, "serbanstein/invoiceextractor") - Notebooks
- Google Colab
- Kaggle
Commit ·
fe19ec3
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Parent(s): f916e23
Upload model
Browse files- adapter_config.json +2 -2
adapter_config.json
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"rank_pattern": {},
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"target_modules": [
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"task_type": "CAUSAL_LM"
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}
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"task_type": "CAUSAL_LM"
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}
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