Instructions to use sarthak247/codellama-7b-humaneval-java-fim with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use sarthak247/codellama-7b-humaneval-java-fim with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/hpcfs/users/a1232991/Sarthak/CodeLLaMA/models/CodeLlama-7b-hf/") model = PeftModel.from_pretrained(base_model, "sarthak247/codellama-7b-humaneval-java-fim") - Notebooks
- Google Colab
- Kaggle
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README.md
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# codellama-7b-humaneval-java-fim
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This model was trained from scratch on an
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It achieves the following results on the evaluation set:
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- Loss: 0.6155
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## Model description
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## Intended uses & limitations
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## Training and evaluation data
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## Training procedure
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# codellama-7b-humaneval-java-fim
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This model was trained from scratch on an [this](https://huggingface.co/datasets/sarthak247/humaneval-java-fixed) dataset for FIM task.
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It achieves the following results on the evaluation set:
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- Loss: 0.6155
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## Model description
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Codellama-7b model trained for FIM on Java code dataset.
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## Intended uses & limitations
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Bleh
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## Training and evaluation data
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Dataset mentioned above
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## Training procedure
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