Instructions to use FreedomIntelligence/Apollo-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use FreedomIntelligence/Apollo-7B with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="FreedomIntelligence/Apollo-7B")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("FreedomIntelligence/Apollo-7B")
model = AutoModelForCausalLM.from_pretrained("FreedomIntelligence/Apollo-7B")

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use FreedomIntelligence/Apollo-7B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "FreedomIntelligence/Apollo-7B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "FreedomIntelligence/Apollo-7B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/FreedomIntelligence/Apollo-7B

SGLang

How to use FreedomIntelligence/Apollo-7B with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "FreedomIntelligence/Apollo-7B" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "FreedomIntelligence/Apollo-7B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "FreedomIntelligence/Apollo-7B" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "FreedomIntelligence/Apollo-7B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use FreedomIntelligence/Apollo-7B with Docker Model Runner:
```
docker model run hf.co/FreedomIntelligence/Apollo-7B
```

Apollo-7B / README.md

Xidong

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	---
	license: apache-2.0
	---
	# Multilingual Medicine: Model, Dataset, Benchmark, Code

	Covering English, Chinese, French, Hindi, Spanish, Hindi, Arabic So far


	<p align="center">
	👨🏻‍💻<a href="https://github.com/FreedomIntelligence/Apollo" target="_blank">Github</a> •📃 <a href="https://arxiv.org/abs/2403.03640" target="_blank">Paper</a> • 🌐 <a href="https://apollo.llmzoo.com/" target="_blank">Demo</a> • 🤗 <a href="https://huggingface.co/datasets/FreedomIntelligence/ApolloCorpus" target="_blank">ApolloCorpus</a> • 🤗 <a href="https://huggingface.co/datasets/FreedomIntelligence/XMedbench" target="_blank">XMedBench</a>
	<br> <a href="./README_zh.md"> 中文 </a> \| <a href="./README.md"> English
	</p>

	![Apollo](assets/apollo_medium_final.png)

	## 🌈 Update

	* [2024.04.25] [MedJamba](https://huggingface.co/FreedomIntelligence/Apollo-MedJamba) released, train and evaluation code refer to [repo](https://github.com/FreedomIntelligence/MedJamba).
	* [2024.03.07] [Paper](https://arxiv.org/abs/2403.03640) released.
	* [2024.02.12] <a href="https://huggingface.co/datasets/FreedomIntelligence/ApolloCorpus" target="_blank">ApolloCorpus</a> and <a href="https://huggingface.co/datasets/FreedomIntelligence/XMedbench" target="_blank">XMedBench</a> is published！🎉
	* [2024.01.23] Apollo repo is published！🎉


	## Results
	🤗 <a href="https://huggingface.co/FreedomIntelligence/Apollo-0.5B" target="_blank">Apollo-0.5B</a> • 🤗 <a href="https://huggingface.co/FreedomIntelligence/Apollo-1.8B" target="_blank">Apollo-1.8B</a> • 🤗 <a href="https://huggingface.co/FreedomIntelligence/Apollo-2B" target="_blank">Apollo-2B</a> • 🤗 <a href="https://huggingface.co/FreedomIntelligence/Apollo-6B" target="_blank">Apollo-6B</a> • 🤗 <a href="https://huggingface.co/FreedomIntelligence/Apollo-7B" target="_blank">Apollo-7B</a> • 🤗 <a href="https://huggingface.co/FreedomIntelligence/Apollo-34B" target="_blank">Apollo-34B</a> • 🤗 <a href="https://huggingface.co/FreedomIntelligence/Apollo-72B" target="_blank">Apollo-72B</a>

	🤗 <a href="https://huggingface.co/FreedomIntelligence/Apollo-MedJamba" target="_blank">MedJamba</a>

	🤗 <a href="https://huggingface.co/FreedomIntelligence/Apollo-0.5B-GGUF" target="_blank">Apollo-0.5B-GGUF</a> • 🤗 <a href="https://huggingface.co/FreedomIntelligence/Apollo-2B-GGUF" target="_blank">Apollo-2B-GGUF</a> • 🤗 <a href="https://huggingface.co/FreedomIntelligence/Apollo-6B-GGUF" target="_blank">Apollo-6B-GGUF</a> • 🤗 <a href="https://huggingface.co/FreedomIntelligence/Apollo-7B-GGUF" target="_blank">Apollo-7B-GGUF</a>



	![Apollo](assets/result.png)


	## Usage Format

	User:{query}\nAssistant:{response}<\|endoftext\|>



	## Dataset & Evaluation

	- Dataset
	🤗 <a href="https://huggingface.co/datasets/FreedomIntelligence/ApolloCorpus" target="_blank">ApolloCorpus</a>

	<details><summary>Click to expand</summary>

	![Apollo](assets/dataset.png)

	- [Zip File](https://huggingface.co/datasets/FreedomIntelligence/ApolloCorpus/blob/main/ApolloCorpus.zip)
	- [Data category](https://huggingface.co/datasets/FreedomIntelligence/ApolloCorpus/tree/main/train)
	- Pretrain:
	- data item:
	- json_name: {data_source}_{language}_{data_type}.json
	- data_type: medicalBook, medicalGuideline, medicalPaper, medicalWeb(from online forum), medicalWiki
	- language: en(English), zh(chinese), es(spanish), fr(french), hi(Hindi)
	- data_type: qa(generated qa from text)
	- data_type==text: list of string
	```
	[
	"string1",
	"string2",
	...
	]
	```
	- data_type==qa: list of qa pairs(list of string)
	```
	[
	[
	"q1",
	"a1",
	"q2",
	"a2",
	...
	],
	...
	]
	```
	- SFT:
	- json_name: {data_source}_{language}.json
	- data_type: code, general, math, medicalExam, medicalPatient
	- data item: list of qa pairs(list of string)
	```
	[
	[
	"q1",
	"a1",
	"q2",
	"a2",
	...
	],
	...
	]
	```


	</details>



	- Evaluation
	🤗 <a href="https://huggingface.co/datasets/FreedomIntelligence/XMedbench" target="_blank">XMedBench</a>

	<details><summary>Click to expand</summary>

	- EN:
	- [MedQA-USMLE](https://huggingface.co/datasets/GBaker/MedQA-USMLE-4-options)
	- [MedMCQA](https://huggingface.co/datasets/medmcqa/viewer/default/test)
	- [PubMedQA](https://huggingface.co/datasets/pubmed_qa): Because the results fluctuated too much, they were not used in the paper.
	- [MMLU-Medical](https://huggingface.co/datasets/cais/mmlu)
	- Clinical knowledge, Medical genetics, Anatomy, Professional medicine, College biology, College medicine
	- ZH:
	- [MedQA-MCMLE](https://huggingface.co/datasets/bigbio/med_qa/viewer/med_qa_zh_4options_bigbio_qa/test)
	- [CMB-single](https://huggingface.co/datasets/FreedomIntelligence/CMB): Not used in the paper
	- Randomly sample 2,000 multiple-choice questions with single answer.
	- [CMMLU-Medical](https://huggingface.co/datasets/haonan-li/cmmlu)
	- Anatomy, Clinical_knowledge, College_medicine, Genetics, Nutrition, Traditional_chinese_medicine, Virology
	- [CExam](https://github.com/williamliujl/CMExam): Not used in the paper
	- Randomly sample 2,000 multiple-choice questions


	- ES: [Head_qa](https://huggingface.co/datasets/head_qa)
	- FR: [Frenchmedmcqa](https://github.com/qanastek/FrenchMedMCQA)
	- HI: [MMLU_HI](https://huggingface.co/datasets/FreedomIntelligence/MMLU_Arabic)
	- Clinical knowledge, Medical genetics, Anatomy, Professional medicine, College biology, College medicine
	- AR: [MMLU_Ara](https://huggingface.co/datasets/FreedomIntelligence/MMLU_Hindi)
	- Clinical knowledge, Medical genetics, Anatomy, Professional medicine, College biology, College medicine


	</details>


	## Results reproduction
	<details><summary>Click to expand</summary>

	Waiting for Update



	</details>




	## Citation
	Please use the following citation if you intend to use our dataset for training or evaluation:

	```
	@misc{wang2024apollo,
	title={Apollo: Lightweight Multilingual Medical LLMs towards Democratizing Medical AI to 6B People},
	author={Xidong Wang and Nuo Chen and Junyin Chen and Yan Hu and Yidong Wang and Xiangbo Wu and Anningzhe Gao and Xiang Wan and Haizhou Li and Benyou Wang},
	year={2024},
	eprint={2403.03640},
	archivePrefix={arXiv},
	primaryClass={cs.CL}
	}
	```