Instructions to use sandeeprdy1729/thrisul-parser with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use sandeeprdy1729/thrisul-parser with Transformers:

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

pipe = pipeline("image-text-to-text", model="sandeeprdy1729/thrisul-parser", trust_remote_code=True)
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 AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("sandeeprdy1729/thrisul-parser", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use sandeeprdy1729/thrisul-parser with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "sandeeprdy1729/thrisul-parser"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "sandeeprdy1729/thrisul-parser",
		"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/sandeeprdy1729/thrisul-parser

SGLang

How to use sandeeprdy1729/thrisul-parser 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 "sandeeprdy1729/thrisul-parser" \
    --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": "sandeeprdy1729/thrisul-parser",
		"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 "sandeeprdy1729/thrisul-parser" \
        --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": "sandeeprdy1729/thrisul-parser",
		"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 sandeeprdy1729/thrisul-parser with Docker Model Runner:
```
docker model run hf.co/sandeeprdy1729/thrisul-parser
```

thrisul-parser / Dockerfile

sandeeprdy1729

Thrisul-Parser v0.1

37fb2b9 verified 16 days ago

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1.39 kB

# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: OpenMDW-1.1

FROM vllm/vllm-openai:v0.26.0
LABEL org.opencontainers.image.title="Nemotron 3.5 Parse" \
      org.opencontainers.image.version="3.5.0.post7" \
      org.opencontainers.image.licenses="OpenMDW-1.1"
WORKDIR /workspace
RUN python3 -m venv /opt/nemotron-parse-venv
ENV PATH="/opt/nemotron-parse-venv/bin:$PATH" \
    VIRTUAL_ENV="/opt/nemotron-parse-venv" \
    PYTHONPATH=""
COPY pyproject.toml LICENSE THIRD_PARTY_NOTICES.md TOKENIZER_ATTRIBUTION.md postprocessing.py latex2html.py /tmp/nemotron-package/
COPY nemotron_parse /tmp/nemotron-package/nemotron_parse
COPY vllm_tied_patch /tmp/nemotron-package/vllm_tied_patch
RUN python3 -m pip install "/tmp/nemotron-package[vllm,client]" && python3 -m pip check
COPY . /workspace
ENTRYPOINT ["python3", "-m", "vllm.entrypoints.openai.api_server"]
CMD ["--model", "/workspace", "--served-model-name", "nemotron-parse", "--trust-remote-code", "--dtype", "bfloat16", "--distributed-executor-backend", "uni", "--tensor-parallel-size", "1", "--max-model-len", "16384", "--max-num-seqs", "192", "--max-num-batched-tokens", "16384", "--no-enable-prefix-caching", "--attention-config", "{\"flash_attn_version\":3}", "--limit-mm-per-prompt", "{\"image\":1}", "--chat-template", "/workspace/chat_template.jinja"]

	# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
	# SPDX-License-Identifier: OpenMDW-1.1

	FROM vllm/vllm-openai:v0.26.0
	LABEL org.opencontainers.image.title="Nemotron 3.5 Parse" \
	org.opencontainers.image.version="3.5.0.post7" \
	org.opencontainers.image.licenses="OpenMDW-1.1"
	WORKDIR /workspace
	RUN python3 -m venv /opt/nemotron-parse-venv
	ENV PATH="/opt/nemotron-parse-venv/bin:$PATH" \
	VIRTUAL_ENV="/opt/nemotron-parse-venv" \
	PYTHONPATH=""
	COPY pyproject.toml LICENSE THIRD_PARTY_NOTICES.md TOKENIZER_ATTRIBUTION.md postprocessing.py latex2html.py /tmp/nemotron-package/
	COPY nemotron_parse /tmp/nemotron-package/nemotron_parse
	COPY vllm_tied_patch /tmp/nemotron-package/vllm_tied_patch
	RUN python3 -m pip install "/tmp/nemotron-package[vllm,client]" && python3 -m pip check
	COPY . /workspace
	ENTRYPOINT ["python3", "-m", "vllm.entrypoints.openai.api_server"]
	CMD ["--model", "/workspace", "--served-model-name", "nemotron-parse", "--trust-remote-code", "--dtype", "bfloat16", "--distributed-executor-backend", "uni", "--tensor-parallel-size", "1", "--max-model-len", "16384", "--max-num-seqs", "192", "--max-num-batched-tokens", "16384", "--no-enable-prefix-caching", "--attention-config", "{\"flash_attn_version\":3}", "--limit-mm-per-prompt", "{\"image\":1}", "--chat-template", "/workspace/chat_template.jinja"]