How to use from
vLLM
Install from pip and serve model
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "iamplus/mpt-30b-v5"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "iamplus/mpt-30b-v5",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'
Use Docker
docker model run hf.co/iamplus/mpt-30b-v5
Quick Links

Base Model : manojpreveen/mpt-30b-v4

Tool : MosaicML's llm-foundry (https://github.com/mosaicml/llm-foundry)

Dataset : Entire flan1m-GPT4 dataset

Config yaml with Model Params : https://huggingface.co/manojpreveen/mpt-30b-v5/blob/main/mpt-30b_v5.yaml

Description : mosaicml/mpt-30b -> Finetuning on (Entire flan3m-GPT3.5 dataset for 4 epochs) iamplus/mpt-30b-v4 -> Finetuning on (Entire flan1m-GPT4 dataset for 4 epochs) -> iamplus/mpt-30b-v5

Prompt Format :

<system>: [system prompt]

<human>: [question]

<bot>:
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Dataset used to train iamplus/mpt-30b-v5