Instructions to use Pranabit/finetune_starcoder2_3b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Pranabit/finetune_starcoder2_3b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("bigcode/starcoder2-3b") model = PeftModel.from_pretrained(base_model, "Pranabit/finetune_starcoder2_3b") - Notebooks
- Google Colab
- Kaggle
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## Model description
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## Intended uses & limitations
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## Model description
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StarCoder2-3B model is a 3B parameter model trained on 17 programming languages from The Stack v2, with opt-out requests excluded. The model uses Grouped Query Attention, a context window of 16,384 tokens with a sliding window attention of 4,096 tokens, and was trained using the Fill-in-the-Middle objective on 3+ trillion tokens.
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## Intended uses & limitations
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