SebastianSchramm_-_Cerebras-GPT-111M-instruction-8bits

Quantization made by Richard Erkhov.

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Cerebras-GPT-111M-instruction - bnb 8bits

• Model creator: https://huggingface.co/SebastianSchramm/
• Original model: https://huggingface.co/SebastianSchramm/Cerebras-GPT-111M-instruction/

Original model description:

language:

• en pipeline_tag: text-generation library_name: transformers tags:
• cerebras
• LLM inference: false base_model: cerebras/Cerebras-GPT-111M

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Instruction-tuned Cerebras GPT 111M

The smallest of cerebras GPT models with only 111M parameters instruction fine-tuned.

Model Description

Instruction fine-tuned cerebras-GPT-111M

Evaluation

The model has been evaluated with Huggingface's Open LLM leaderboard. Have a look at the leaderboard for more details: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard The performance of the instruction fine-tuned model does improve compared to the cerebras base model by about 5.7% (average score):

Training data

The model was fine-tuned with the following data: alpaca_gpt4_data (data generated by GPT-4 using Alpaca prompts for fine-tuning LLMs) and alpaca_data_cleaned.

Prompt template

Fine-tuning was performed with the promp template from stanford alpaca:

PROMPT_DICT = {
    "prompt_input": (
        "Below is an instruction that describes a task, paired with an input that provides further context. "
        "Write a response that appropriately completes the request.\n\n"
        "### Instruction:\n{instruction}\n\n### Input:\n{input}\n\n### Response:"
    ),
    "prompt_no_input": (
        "Below is an instruction that describes a task. "
        "Write a response that appropriately completes the request.\n\n"
        "### Instruction:\n{instruction}\n\n### Response:"
    ),
}

Usage

It is recommended to format input according to the prompt template mentioned above during inference for best results.