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Update README with ZenML namespace dataset and repository links
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llm-finetuning/README.md

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@@ -127,7 +127,7 @@ python run.py --deployment-pipeline --config deployment_a100.yaml
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A working prototype has been trained and deployed as of Jan 19 2024. The model is using minimal data and finetuned using QLoRA and PEFT. The model was trained using 1 A100 GPU on the cloud:
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- Training dataset [Link](https://huggingface.co/datasets/htahir1/zenml-codegen-v1)
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- Training dataset [Link](https://huggingface.co/datasets/zenml/zenml-codegen-v1)
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- PEFT Model [Link](https://huggingface.co/htahir1/peft-lora-zencoder15B-personal-copilot/)
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- Fully merged model (Ready to deploy on HuggingFace Inference Endpoints) [Link](https://huggingface.co/htahir1/peft-lora-zencoder15B-personal-copilot-merged)
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This project recently did a [call of volunteers](https://www.linkedin.com/feed/update/urn:li:activity:7150388250178662400/). This TODO list can serve as a source of collaboration. If you want to work on any of the following, please [create an issue on this repository](https://github.com/zenml-io/zenml-projects/issues) and assign it to yourself!
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- [x] Create a functioning data generation pipeline (initial dataset with the core [ZenML repo](https://github.com/zenml-io/zenml) scraped and pushed [here](https://huggingface.co/datasets/htahir1/zenml-codegen-v1))
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- [x] Create a functioning data generation pipeline (initial dataset with the core [ZenML repo](https://github.com/zenml-io/zenml) scraped and pushed [here](https://huggingface.co/datasets/zenml/zenml-codegen-v1))
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- [x] Deploy the model on a HuggingFace inference endpoint and use it in the [VS Code Extension](https://github.com/huggingface/llm-vscode#installation) using a deployment pipeline.
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- [x] Create a functioning training pipeline.
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- [ ] Curate a set of 5-10 repositories that are using the ZenML latest syntax and use data generation pipeline to push dataset to HuggingFace.

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