Instructions to use monsterapi/mistral_7b_HalfEpoch_DolphinCoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use monsterapi/mistral_7b_HalfEpoch_DolphinCoder with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-v0.1") model = PeftModel.from_pretrained(base_model, "monsterapi/mistral_7b_HalfEpoch_DolphinCoder") - Notebooks
- Google Colab
- Kaggle
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README.md
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With the utilization of [MonsterAPI](https://monsterapi.ai)'s [no-code LLM finetuner](https://monsterapi.ai/finetuning), this finetuning:
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- Was achieved with great cost-effectiveness.
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- Completed in a total duration of 7hrs 36min for 0.
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- Costed `$15.2` for the entire run
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#### Hyperparameters & Additional Details:
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- **Epochs:** 0.
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- **Cost for full run:** $15.2
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- **Model Path:** mistralai/Mistral-7B-v0.1
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- **Learning Rate:** 0.0002
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With the utilization of [MonsterAPI](https://monsterapi.ai)'s [no-code LLM finetuner](https://monsterapi.ai/finetuning), this finetuning:
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- Was achieved with great cost-effectiveness.
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- Completed in a total duration of 7hrs 36min for 0.5 epochs using an A6000 48GB GPU.
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- Costed `$15.2` for the entire run
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#### Hyperparameters & Additional Details:
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- **Epochs:** 0.5
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- **Cost for full run:** $15.2
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- **Model Path:** mistralai/Mistral-7B-v0.1
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- **Learning Rate:** 0.0002
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