PEFT
llama2
llama2-7b
code generation
code-generation
code
instruct
instruct-code
code-alpaca
alpaca-instruct
alpaca
llama7b
gpt2
Instructions to use monsterapi/llama2-code-generation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use monsterapi/llama2-code-generation with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-7b-hf") model = PeftModel.from_pretrained(base_model, "monsterapi/llama2-code-generation") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Add base_model information to model
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README.md
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- nampdn-ai/tiny-codes
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library_name: peft
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tags:
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- llama2
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- alpaca
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- llama7b
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- gpt2
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---
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## Training procedure
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We finetuned [Llama 2 7B model](https://huggingface.co/meta-llama/Llama-2-7b-hf) from Meta on [nampdn-ai/tiny-codes](https://huggingface.co/datasets/nampdn-ai/tiny-codes) for ~ 10,000 steps using [MonsterAPI](https://monsterapi.ai) no-code [LLM finetuner](https://docs.monsterapi.ai/fine-tune-a-large-language-model-llm).
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---
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license: apache-2.0
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library_name: peft
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tags:
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- llama2
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- alpaca
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- llama7b
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- gpt2
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datasets:
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- nampdn-ai/tiny-codes
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base_model: meta-llama/Llama-2-7b-hf
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---
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## Training procedure
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We finetuned [Llama 2 7B model](https://huggingface.co/meta-llama/Llama-2-7b-hf) from Meta on [nampdn-ai/tiny-codes](https://huggingface.co/datasets/nampdn-ai/tiny-codes) for ~ 10,000 steps using [MonsterAPI](https://monsterapi.ai) no-code [LLM finetuner](https://docs.monsterapi.ai/fine-tune-a-large-language-model-llm).
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