Librarian Bot: Add base_model information to model
Browse filesThis pull request aims to enrich the metadata of your model by adding [`EleutherAI/gpt-j-6b`](https://huggingface.co/EleutherAI/gpt-j-6b) as a `base_model` field, situated in the `YAML` block of your model's `README.md`.
How did we find this information? We extracted this infromation from the `adapter_config.json` file of your model.
**Why add this?** Enhancing your model's metadata in this way:
- **Boosts Discoverability** - It becomes straightforward to trace the relationships between various models on the Hugging Face Hub.
- **Highlights Impact** - It showcases the contributions and influences different models have within the community.
For a hands-on example of how such metadata can play a pivotal role in mapping model connections, take a look at [librarian-bots/base_model_explorer](https://huggingface.co/spaces/librarian-bots/base_model_explorer).
This PR comes courtesy of [Librarian Bot](https://huggingface.co/librarian-bot). If you have any feedback, queries, or need assistance, please don't hesitate to reach out to [@davanstrien](https://huggingface.co/davanstrien).
If you want to automatically add `base_model` metadata to more of your modes you can use the [Librarian Bot](https://huggingface.co/librarian-bot) [Metadata Request Service](https://huggingface.co/spaces/librarian-bots/metadata_request_service)!
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---
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license: apache-2.0
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datasets:
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- vicgalle/alpaca-gpt4
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pipeline_tag: conversational
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tags:
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- alpaca
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- gpt4
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- finetuning
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- lora
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- peft
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---
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GPT-J 6B model was finetuned on GPT-4 generations of the Alpaca prompts on [MonsterAPI](https://monsterapi.ai)'s no-code LLM finetuner, using LoRA for ~ 65,000 steps, auto-optmised to run on 1 A6000 GPU with no out of memory issues and without needing me to write any code or setup a GPU server with libraries to run this experiment. The finetuner does it all for us by itself.
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---
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license: apache-2.0
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tags:
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- alpaca
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- gpt4
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- finetuning
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- lora
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- peft
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datasets:
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- vicgalle/alpaca-gpt4
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pipeline_tag: conversational
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base_model: EleutherAI/gpt-j-6b
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---
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GPT-J 6B model was finetuned on GPT-4 generations of the Alpaca prompts on [MonsterAPI](https://monsterapi.ai)'s no-code LLM finetuner, using LoRA for ~ 65,000 steps, auto-optmised to run on 1 A6000 GPU with no out of memory issues and without needing me to write any code or setup a GPU server with libraries to run this experiment. The finetuner does it all for us by itself.
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