Instructions to use monkeypostulate/gpt-neo-1.3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use monkeypostulate/gpt-neo-1.3B with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.2-1B-Instruct") model = PeftModel.from_pretrained(base_model, "monkeypostulate/gpt-neo-1.3B") - Notebooks
- Google Colab
- Kaggle
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Verified signatureThis model is a fine-tuned version of [meta-llama/Llama-3.2-1B, optimized with ORPO (Optimized Regularization for Prompt Optimization) Trainer. Fine-tuning was performed using a subset of the [meta-llama/Llama-3.2-1B dataset, with only 100 samples selected to enable rapid training with ORPO’s efficient approach. **Fine-tuning Method:** ORPO **Dataset:** mlabonne/orpo-dpo-mix-40k **Evaluation** The model was evaluated on the following benchmarks, with the following performance metrics: | Tasks |Version|Filter|n-shot| Metric | |Value | |Stderr| |---------|------:|------|-----:|--------|---|-----:|---|-----:| |hellaswag| 1|none | 0|acc |↑ | 0.4772 |± | 0.0050 | | | |none | 0|acc_norm|↑ |0.6366 |± | 0.0048 |3be466d
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