Instructions to use WootzappLab/fara-9b-baseline-eval with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use WootzappLab/fara-9b-baseline-eval with Transformers:

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

pipe = pipeline("image-text-to-text", model="WootzappLab/fara-9b-baseline-eval")
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("WootzappLab/fara-9b-baseline-eval")
model = AutoModelForMultimodalLM.from_pretrained("WootzappLab/fara-9b-baseline-eval", 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 WootzappLab/fara-9b-baseline-eval with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "WootzappLab/fara-9b-baseline-eval"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "WootzappLab/fara-9b-baseline-eval",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/WootzappLab/fara-9b-baseline-eval

SGLang

How to use WootzappLab/fara-9b-baseline-eval 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 "WootzappLab/fara-9b-baseline-eval" \
    --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": "WootzappLab/fara-9b-baseline-eval",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

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 "WootzappLab/fara-9b-baseline-eval" \
        --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": "WootzappLab/fara-9b-baseline-eval",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Docker Model Runner
How to use WootzappLab/fara-9b-baseline-eval with Docker Model Runner:
```
docker model run hf.co/WootzappLab/fara-9b-baseline-eval
```

fara-9b-baseline-eval / MANIFEST.json

ishagarg1103

Correct dataset and execution environment provenance

6b15345 verified 24 days ago

Raw History Blame Contribute Delete

1.56 kB

	{
	"schema_version": 1,
	"repository": "WootzappLab/fara-9b-baseline-eval",
	"publisher": "IshaGarg1103",
	"published_at": "2026-09-25",
	"checkpoint": {
	"source_repository": "microsoft/Fara1.5-9B",
	"source_revision": "1a93677cd89d5601bc2ed759791e981f3a520032",
	"weights_modified": false,
	"license": "MIT"
	},
	"source": {
	"fara_repository": "https://github.com/microsoft/fara",
	"fara_revision": "a675d6d61c41c47ae87bacefeab22caad18e3e84",
	"dataset_repository": "https://huggingface.co/datasets/WootzappLab/cua-bench",
	"dataset_revision": "745eebb8f07abb92fdaae356bb6bee3a1f2975af",
	"recorder_harness_repository": "https://github.com/tokenbender/w8-cua-bench",
	"recorder_harness_branch": "environment-work",
	"recorder_harness_revision": "66037db6bae4b00a2b5860aa08ebb69b559e6871",
	"environment_revision": "66037db6bae4b00a2b5860aa08ebb69b559e6871",
	"verifier_revision": "66037db6bae4b00a2b5860aa08ebb69b559e6871",
	"infrastructure_revision": null,
	"infrastructure_status": "pending branch push and pull request"
	},
	"evaluation": {
	"run_id": "fara15-dom-baseline",
	"date": "2026-09-25",
	"gcp_instance": "w8-fara-9b-8115f370-head-3ibtw2ah-compute",
	"selected_tasks": 90,
	"passed": 6,
	"verified_failed": 60,
	"verified_tasks": 66,
	"execution_errors": 24,
	"infrastructure_errors": 0,
	"pass_at_1": 0.06666666666666667,
	"verified_pass_rate": 0.09090909090909091,
	"artifact_status": "pending upload",
	"results_report_status": "pending"
	}
	}