Instructions to use FreedomIntelligence/Apollo-0.5B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use FreedomIntelligence/Apollo-0.5B with Transformers:

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

pipe = pipeline("text-generation", model="FreedomIntelligence/Apollo-0.5B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("FreedomIntelligence/Apollo-0.5B")
model = AutoModelForCausalLM.from_pretrained("FreedomIntelligence/Apollo-0.5B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use FreedomIntelligence/Apollo-0.5B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "FreedomIntelligence/Apollo-0.5B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "FreedomIntelligence/Apollo-0.5B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/FreedomIntelligence/Apollo-0.5B

SGLang

How to use FreedomIntelligence/Apollo-0.5B 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-0.5B" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "FreedomIntelligence/Apollo-0.5B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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-0.5B" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "FreedomIntelligence/Apollo-0.5B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use FreedomIntelligence/Apollo-0.5B with Docker Model Runner:
```
docker model run hf.co/FreedomIntelligence/Apollo-0.5B
```

Xidong commited on Mar 7, 2024

Commit

2a71ddf

verified ·

1 Parent(s): 91303f9

Update README.md

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@@ -7,7 +7,7 @@ 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="" 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>
@@ -32,10 +32,93 @@ Covering English, Chinese, French, Hindi, Spanish, Hindi, Arabic So far
 ## Dataset & Evaluation
 - Dataset
-  🤗 <a href="https://huggingface.co/datasets/FreedomIntelligence/ApolloCorpus" target="_blank">ApolloCorpus</a>
 - Evaluation
-  🤗 <a href="https://huggingface.co/datasets/FreedomIntelligence/XMedbench" target="_blank">XMedBench</a>
 ## Results reproduction

 <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>
 ## 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/Medbase_data/blob/main/Medbase_data-datasets.zip)
+    - [Data category](https://huggingface.co/datasets/FreedomIntelligence/Medbase_data/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