Instructions to use HoomanBio2021/LabOpen-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use HoomanBio2021/LabOpen-v1 with Transformers:

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

pipe = pipeline("text-generation", model="HoomanBio2021/LabOpen-v1")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("HoomanBio2021/LabOpen-v1")
model = AutoModelForMultimodalLM.from_pretrained("HoomanBio2021/LabOpen-v1", device_map="auto")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
inputs = processor.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=256)
print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use HoomanBio2021/LabOpen-v1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "HoomanBio2021/LabOpen-v1"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "HoomanBio2021/LabOpen-v1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/HoomanBio2021/LabOpen-v1

SGLang

How to use HoomanBio2021/LabOpen-v1 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 "HoomanBio2021/LabOpen-v1" \
    --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": "HoomanBio2021/LabOpen-v1",
		"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 "HoomanBio2021/LabOpen-v1" \
        --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": "HoomanBio2021/LabOpen-v1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use HoomanBio2021/LabOpen-v1 with Docker Model Runner:
```
docker model run hf.co/HoomanBio2021/LabOpen-v1
```

HoomanBio commited on 2 days ago

Commit

8e2a0ef

verified ·

1 Parent(s): 64b9bd8

Update README.md

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README.md +12 -12

README.md CHANGED Viewed

@@ -18,7 +18,7 @@ library_name: transformers
 pipeline_tag: text-generation
 ---
-# Qwen3.8-27B-LabOpen v1
 Qwen3.8-27B strengthened for verifiable scientific computation — released both as **merged FP8 full weights** (drop-in for the base) and as the original **LoRA adapter**.
@@ -31,7 +31,7 @@ LabOpen v1 adds six verifiable capability domains (fluid physics, materials mixt
 ## Positioning & Philosophy
-Qwen3.8-27B-LabOpen v1 is a research model built on the open Qwen3.8-27B foundation through domain fine-tuning and optimization, focused on scientific research fields including programming, physics, life sciences, and materials science.
 The project does not aim to replace general-purpose large language models. It seeks to preserve the comprehensive strengths of a general model while further strengthening its adaptation to scientific knowledge, domain-specific problems, and research workloads.
@@ -102,8 +102,8 @@ The five external-comparison models above were also run on the **domain heldout
 ### Serving the merged weights (recommended)
 ```bash
-vllm serve HoomanBio2021/Qwen3.8-27B-LabOpen-v1
-# or: docker run ... vllm/vllm-openai --model HoomanBio2021/Qwen3.8-27B-LabOpen-v1
 ```
 The merged checkpoint uses the same blockwise FP8 (e4m3, 128×128 scales) format as the base — any runtime that loads `Qwen/Qwen3.8-27B-FP8` loads this without changes.
@@ -182,10 +182,10 @@ We thank these teams for pushing open, measurable frontiers — this release aim
 ```bibtex
 @software{labopen_v1,
-  title = {Qwen3.8-27B-LabOpen v1: Six-Domain Reinforcement of Qwen3.8-27B},
   author = {Hooman AI Lab},
   year = {2026},
-  url = {https://huggingface.co/HoomanBio2021/Qwen3.8-27B-LabOpen-v1},
   base = {Qwen/Qwen3.8-27B-FP8},
   license = {Apache-2.0}
 }
@@ -199,7 +199,7 @@ If you have any questions, please raise an issue or contact us at [service@hooma
 # 中文版模型卡
-# Qwen3.8-27B-LabOpen v1
 面向可验证科学计算强化的 Qwen3.8-27B——同时以**合并 FP8 全权重**（与基座即插即用）与原始 **LoRA 适配器**两种形态发布。
@@ -212,7 +212,7 @@ LabOpen v1 在 [Qwen/Qwen3.8-27B-FP8](https://huggingface.co/Qwen/Qwen3.8-27B-FP
 ## 项目定位与理念
-Qwen3.8-27B-LabOpen v1 是基于 Qwen3.8-27B 开源基础模型开展领域微调与优化的研究模型，重点面向编程、物理学、生命科学、材料科学等科学研究领域。
 项目并不以取代通用大模型为目标，而是希望在保留通用模型综合能力的基础上，进一步增强其对科学专业知识、领域问题及研究任务的适应能力。
@@ -283,8 +283,8 @@ Qwen3.8-27B-LabOpen v1 是基于 Qwen3.8-27B 开源基础模型开展领域微
 ### 部署合并权重（推荐）
 ```bash
-vllm serve HoomanBio2021/Qwen3.8-27B-LabOpen-v1
-# 或：docker run ... vllm/vllm-openai --model HoomanBio2021/Qwen3.8-27B-LabOpen-v1
 ```
 合并检查点与基座采用完全相同的分块 FP8（e4m3，128×128 块尺度）格式——任何能加载 `Qwen/Qwen3.8-27B-FP8` 的运行时均可直接加载本仓库，无需改动。
@@ -363,10 +363,10 @@ vllm serve HoomanBio2021/Qwen3.8-27B-LabOpen-v1
 ```bibtex
 @software{labopen_v1,
-  title = {Qwen3.8-27B-LabOpen v1: Six-Domain Reinforcement of Qwen3.8-27B},
   author = {Hooman AI Lab},
   year = {2026},
-  url = {https://huggingface.co/HoomanBio2021/Qwen3.8-27B-LabOpen-v1},
   base = {Qwen/Qwen3.8-27B-FP8},
   license = {Apache-2.0}
 }

 pipeline_tag: text-generation
 ---
+# LabOpen v1
 Qwen3.8-27B strengthened for verifiable scientific computation — released both as **merged FP8 full weights** (drop-in for the base) and as the original **LoRA adapter**.
 ## Positioning & Philosophy
+LabOpen v1 is a research model built on the open Qwen3.8-27B foundation through domain fine-tuning and optimization, focused on scientific research fields including programming, physics, life sciences, and materials science.
 The project does not aim to replace general-purpose large language models. It seeks to preserve the comprehensive strengths of a general model while further strengthening its adaptation to scientific knowledge, domain-specific problems, and research workloads.
 ### Serving the merged weights (recommended)
 ```bash
+vllm serve HoomanBio2021/LabOpen-v1
+# or: docker run ... vllm/vllm-openai --model HoomanBio2021/LabOpen-v1
 ```
 The merged checkpoint uses the same blockwise FP8 (e4m3, 128×128 scales) format as the base — any runtime that loads `Qwen/Qwen3.8-27B-FP8` loads this without changes.
 ```bibtex
 @software{labopen_v1,
+  title = {LabOpen v1: Six-Domain Reinforcement of Qwen3.8-27B},
   author = {Hooman AI Lab},
   year = {2026},
+  url = {https://huggingface.co/HoomanBio2021/LabOpen-v1},
   base = {Qwen/Qwen3.8-27B-FP8},
   license = {Apache-2.0}
 }
 # 中文版模型卡
+# LabOpen v1
 面向可验证科学计算强化的 Qwen3.8-27B——同时以**合并 FP8 全权重**（与基座即插即用）与原始 **LoRA 适配器**两种形态发布。
 ## 项目定位与理念
+LabOpen v1 是基于 Qwen3.8-27B 开源基础模型开展领域微调与优化的研究模型，重点面向编程、物理学、生命科学、材料科学等科学研究领域。
 项目并不以取代通用大模型为目标，而是希望在保留通用模型综合能力的基础上，进一步增强其对科学专业知识、领域问题及研究任务的适应能力。
 ### 部署合并权重（推荐）
 ```bash
+vllm serve HoomanBio2021/LabOpen-v1
+# 或：docker run ... vllm/vllm-openai --model HoomanBio2021/LabOpen-v1
 ```
 合并检查点与基座采用完全相同的分块 FP8（e4m3，128×128 块尺度）格式——任何能加载 `Qwen/Qwen3.8-27B-FP8` 的运行时均可直接加载本仓库，无需改动。
 ```bibtex
 @software{labopen_v1,
+  title = {LabOpen v1: Six-Domain Reinforcement of Qwen3.8-27B},
   author = {Hooman AI Lab},
   year = {2026},
+  url = {https://huggingface.co/HoomanBio2021/LabOpen-v1},
   base = {Qwen/Qwen3.8-27B-FP8},
   license = {Apache-2.0}
 }