Image-Text-to-Text
Transformers
Safetensors
qwen2_5_vl
llama-factory
full
Generated from Trainer
conversational
text-generation-inference
Instructions to use Eustia1/OmniCoT-R1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Eustia1/OmniCoT-R1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="Eustia1/OmniCoT-R1") 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)# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("Eustia1/OmniCoT-R1") model = AutoModelForMultimodalLM.from_pretrained("Eustia1/OmniCoT-R1") 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=40) print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Eustia1/OmniCoT-R1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Eustia1/OmniCoT-R1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Eustia1/OmniCoT-R1", "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/Eustia1/OmniCoT-R1
- SGLang
How to use Eustia1/OmniCoT-R1 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 "Eustia1/OmniCoT-R1" \ --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": "Eustia1/OmniCoT-R1", "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 "Eustia1/OmniCoT-R1" \ --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": "Eustia1/OmniCoT-R1", "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 Eustia1/OmniCoT-R1 with Docker Model Runner:
docker model run hf.co/Eustia1/OmniCoT-R1
| {"current_steps": 10, "total_steps": 2700, "loss": 1.9059, "lr": 3.3333333333333335e-07, "epoch": 0.011120378092855158, "percentage": 0.37, "elapsed_time": "0:00:53", "remaining_time": "4:01:28"} | |
| {"current_steps": 20, "total_steps": 2700, "loss": 1.8159, "lr": 7.037037037037038e-07, "epoch": 0.022240756185710316, "percentage": 0.74, "elapsed_time": "0:01:43", "remaining_time": "3:50:24"} | |
| {"current_steps": 30, "total_steps": 2700, "loss": 1.5319, "lr": 1.074074074074074e-06, "epoch": 0.03336113427856547, "percentage": 1.11, "elapsed_time": "0:02:32", "remaining_time": "3:45:57"} | |
| {"current_steps": 40, "total_steps": 2700, "loss": 1.2454, "lr": 1.4444444444444445e-06, "epoch": 0.04448151237142063, "percentage": 1.48, "elapsed_time": "0:03:21", "remaining_time": "3:43:25"} | |
| {"current_steps": 50, "total_steps": 2700, "loss": 0.9937, "lr": 1.8148148148148151e-06, "epoch": 0.055601890464275786, "percentage": 1.85, "elapsed_time": "0:04:10", "remaining_time": "3:41:32"} | |
| {"current_steps": 60, "total_steps": 2700, "loss": 0.8582, "lr": 2.1851851851851853e-06, "epoch": 0.06672226855713094, "percentage": 2.22, "elapsed_time": "0:05:00", "remaining_time": "3:40:04"} | |
| {"current_steps": 70, "total_steps": 2700, "loss": 0.8171, "lr": 2.5555555555555557e-06, "epoch": 0.0778426466499861, "percentage": 2.59, "elapsed_time": "0:05:49", "remaining_time": "3:38:43"} | |
| {"current_steps": 80, "total_steps": 2700, "loss": 0.771, "lr": 2.9259259259259257e-06, "epoch": 0.08896302474284126, "percentage": 2.96, "elapsed_time": "0:06:38", "remaining_time": "3:37:33"} | |
| {"current_steps": 90, "total_steps": 2700, "loss": 0.7154, "lr": 3.296296296296296e-06, "epoch": 0.10008340283569642, "percentage": 3.33, "elapsed_time": "0:07:27", "remaining_time": "3:36:24"} | |
| {"current_steps": 100, "total_steps": 2700, "loss": 0.7022, "lr": 3.6666666666666666e-06, "epoch": 0.11120378092855157, "percentage": 3.7, "elapsed_time": "0:08:16", "remaining_time": "3:35:20"} | |
| {"current_steps": 110, "total_steps": 2700, "loss": 0.7072, "lr": 4.037037037037037e-06, "epoch": 0.12232415902140673, "percentage": 4.07, "elapsed_time": "0:09:06", "remaining_time": "3:34:19"} | |
| {"current_steps": 120, "total_steps": 2700, "loss": 0.6981, "lr": 4.407407407407408e-06, "epoch": 0.13344453711426188, "percentage": 4.44, "elapsed_time": "0:09:55", "remaining_time": "3:33:22"} | |
| {"current_steps": 130, "total_steps": 2700, "loss": 0.7073, "lr": 4.777777777777778e-06, "epoch": 0.14456491520711703, "percentage": 4.81, "elapsed_time": "0:10:44", "remaining_time": "3:32:24"} | |
| {"current_steps": 140, "total_steps": 2700, "loss": 0.6806, "lr": 5.148148148148149e-06, "epoch": 0.1556852932999722, "percentage": 5.19, "elapsed_time": "0:11:33", "remaining_time": "3:31:29"} | |
| {"current_steps": 150, "total_steps": 2700, "loss": 0.6597, "lr": 5.518518518518518e-06, "epoch": 0.16680567139282734, "percentage": 5.56, "elapsed_time": "0:12:23", "remaining_time": "3:30:34"} | |
| {"current_steps": 160, "total_steps": 2700, "loss": 0.6366, "lr": 5.88888888888889e-06, "epoch": 0.17792604948568252, "percentage": 5.93, "elapsed_time": "0:13:12", "remaining_time": "3:29:39"} | |
| {"current_steps": 170, "total_steps": 2700, "loss": 0.6623, "lr": 6.259259259259259e-06, "epoch": 0.18904642757853768, "percentage": 6.3, "elapsed_time": "0:14:01", "remaining_time": "3:28:47"} | |
| {"current_steps": 180, "total_steps": 2700, "loss": 0.6669, "lr": 6.62962962962963e-06, "epoch": 0.20016680567139283, "percentage": 6.67, "elapsed_time": "0:14:50", "remaining_time": "3:27:53"} | |
| {"current_steps": 190, "total_steps": 2700, "loss": 0.6763, "lr": 7e-06, "epoch": 0.211287183764248, "percentage": 7.04, "elapsed_time": "0:15:40", "remaining_time": "3:27:01"} | |
| {"current_steps": 200, "total_steps": 2700, "loss": 0.6501, "lr": 7.370370370370371e-06, "epoch": 0.22240756185710314, "percentage": 7.41, "elapsed_time": "0:16:29", "remaining_time": "3:26:09"} | |
| {"current_steps": 210, "total_steps": 2700, "loss": 0.6554, "lr": 7.74074074074074e-06, "epoch": 0.2335279399499583, "percentage": 7.78, "elapsed_time": "0:17:18", "remaining_time": "3:25:17"} | |
| {"current_steps": 220, "total_steps": 2700, "loss": 0.6275, "lr": 8.111111111111112e-06, "epoch": 0.24464831804281345, "percentage": 8.15, "elapsed_time": "0:18:08", "remaining_time": "3:24:28"} | |
| {"current_steps": 230, "total_steps": 2700, "loss": 0.6412, "lr": 8.481481481481482e-06, "epoch": 0.2557686961356686, "percentage": 8.52, "elapsed_time": "0:18:57", "remaining_time": "3:23:37"} | |
| {"current_steps": 240, "total_steps": 2700, "loss": 0.6471, "lr": 8.851851851851853e-06, "epoch": 0.26688907422852376, "percentage": 8.89, "elapsed_time": "0:19:46", "remaining_time": "3:22:45"} | |
| {"current_steps": 250, "total_steps": 2700, "loss": 0.6384, "lr": 9.222222222222224e-06, "epoch": 0.2780094523213789, "percentage": 9.26, "elapsed_time": "0:20:36", "remaining_time": "3:21:54"} | |
| {"current_steps": 260, "total_steps": 2700, "loss": 0.6086, "lr": 9.592592592592593e-06, "epoch": 0.28912983041423407, "percentage": 9.63, "elapsed_time": "0:21:25", "remaining_time": "3:21:04"} | |
| {"current_steps": 270, "total_steps": 2700, "loss": 0.6591, "lr": 9.962962962962964e-06, "epoch": 0.3002502085070892, "percentage": 10.0, "elapsed_time": "0:22:14", "remaining_time": "3:20:12"} | |
| {"current_steps": 280, "total_steps": 2700, "loss": 0.6232, "lr": 9.999661540018812e-06, "epoch": 0.3113705865999444, "percentage": 10.37, "elapsed_time": "0:23:04", "remaining_time": "3:19:22"} | |
| {"current_steps": 290, "total_steps": 2700, "loss": 0.6198, "lr": 9.998491613727142e-06, "epoch": 0.32249096469279953, "percentage": 10.74, "elapsed_time": "0:23:53", "remaining_time": "3:18:31"} | |
| {"current_steps": 300, "total_steps": 2700, "loss": 0.6502, "lr": 9.996486238101964e-06, "epoch": 0.3336113427856547, "percentage": 11.11, "elapsed_time": "0:24:42", "remaining_time": "3:17:40"} | |
| {"current_steps": 310, "total_steps": 2700, "loss": 0.6183, "lr": 9.99364574832234e-06, "epoch": 0.3447317208785099, "percentage": 11.48, "elapsed_time": "0:25:31", "remaining_time": "3:16:49"} | |
| {"current_steps": 320, "total_steps": 2700, "loss": 0.6349, "lr": 9.98997061914855e-06, "epoch": 0.35585209897136505, "percentage": 11.85, "elapsed_time": "0:26:21", "remaining_time": "3:15:59"} | |
| {"current_steps": 330, "total_steps": 2700, "loss": 0.6218, "lr": 9.985461464842748e-06, "epoch": 0.3669724770642202, "percentage": 12.22, "elapsed_time": "0:27:10", "remaining_time": "3:15:08"} | |
| {"current_steps": 340, "total_steps": 2700, "loss": 0.6387, "lr": 9.98011903906629e-06, "epoch": 0.37809285515707536, "percentage": 12.59, "elapsed_time": "0:27:59", "remaining_time": "3:14:17"} | |
| {"current_steps": 350, "total_steps": 2700, "loss": 0.6222, "lr": 9.973944234753763e-06, "epoch": 0.3892132332499305, "percentage": 12.96, "elapsed_time": "0:28:48", "remaining_time": "3:13:27"} | |
| {"current_steps": 360, "total_steps": 2700, "loss": 0.6403, "lr": 9.966938083963747e-06, "epoch": 0.40033361134278567, "percentage": 13.33, "elapsed_time": "0:29:37", "remaining_time": "3:12:36"} | |
| {"current_steps": 370, "total_steps": 2700, "loss": 0.6185, "lr": 9.959101757706308e-06, "epoch": 0.4114539894356408, "percentage": 13.7, "elapsed_time": "0:30:27", "remaining_time": "3:11:46"} | |
| {"current_steps": 380, "total_steps": 2700, "loss": 0.5915, "lr": 9.950436565747286e-06, "epoch": 0.422574367528496, "percentage": 14.07, "elapsed_time": "0:31:16", "remaining_time": "3:10:56"} | |
| {"current_steps": 390, "total_steps": 2700, "loss": 0.6076, "lr": 9.940943956389369e-06, "epoch": 0.43369474562135113, "percentage": 14.44, "elapsed_time": "0:32:05", "remaining_time": "3:10:06"} | |
| {"current_steps": 400, "total_steps": 2700, "loss": 0.6022, "lr": 9.930625516230026e-06, "epoch": 0.4448151237142063, "percentage": 14.81, "elapsed_time": "0:32:55", "remaining_time": "3:09:17"} | |
| {"current_steps": 410, "total_steps": 2700, "loss": 0.6039, "lr": 9.919482969896333e-06, "epoch": 0.45593550180706144, "percentage": 15.19, "elapsed_time": "0:33:44", "remaining_time": "3:08:27"} | |
| {"current_steps": 420, "total_steps": 2700, "loss": 0.5985, "lr": 9.907518179756704e-06, "epoch": 0.4670558798999166, "percentage": 15.56, "elapsed_time": "0:34:33", "remaining_time": "3:07:37"} | |
| {"current_steps": 430, "total_steps": 2700, "loss": 0.5789, "lr": 9.894733145609623e-06, "epoch": 0.47817625799277175, "percentage": 15.93, "elapsed_time": "0:35:22", "remaining_time": "3:06:47"} | |
| {"current_steps": 440, "total_steps": 2700, "loss": 0.6163, "lr": 9.881130004349394e-06, "epoch": 0.4892966360856269, "percentage": 16.3, "elapsed_time": "0:36:12", "remaining_time": "3:05:57"} | |
| {"current_steps": 450, "total_steps": 2700, "loss": 0.6163, "lr": 9.866711029608977e-06, "epoch": 0.5004170141784821, "percentage": 16.67, "elapsed_time": "0:37:01", "remaining_time": "3:05:08"} | |
| {"current_steps": 460, "total_steps": 2700, "loss": 0.6006, "lr": 9.851478631379982e-06, "epoch": 0.5115373922713372, "percentage": 17.04, "elapsed_time": "0:37:50", "remaining_time": "3:04:18"} | |
| {"current_steps": 470, "total_steps": 2700, "loss": 0.5958, "lr": 9.835435355609854e-06, "epoch": 0.5226577703641924, "percentage": 17.41, "elapsed_time": "0:38:40", "remaining_time": "3:03:29"} | |
| {"current_steps": 480, "total_steps": 2700, "loss": 0.5938, "lr": 9.818583883776343e-06, "epoch": 0.5337781484570475, "percentage": 17.78, "elapsed_time": "0:39:29", "remaining_time": "3:02:39"} | |
| {"current_steps": 490, "total_steps": 2700, "loss": 0.6093, "lr": 9.800927032439322e-06, "epoch": 0.5448985265499027, "percentage": 18.15, "elapsed_time": "0:40:18", "remaining_time": "3:01:49"} | |
| {"current_steps": 500, "total_steps": 2700, "loss": 0.6116, "lr": 9.78246775277003e-06, "epoch": 0.5560189046427578, "percentage": 18.52, "elapsed_time": "0:41:08", "remaining_time": "3:00:59"} | |
| {"current_steps": 510, "total_steps": 2700, "loss": 0.5851, "lr": 9.763209130057807e-06, "epoch": 0.567139282735613, "percentage": 18.89, "elapsed_time": "0:41:57", "remaining_time": "3:00:09"} | |
| {"current_steps": 520, "total_steps": 2700, "loss": 0.5736, "lr": 9.743154383194422e-06, "epoch": 0.5782596608284681, "percentage": 19.26, "elapsed_time": "0:42:46", "remaining_time": "2:59:20"} | |
| {"current_steps": 530, "total_steps": 2700, "loss": 0.6007, "lr": 9.722306864136064e-06, "epoch": 0.5893800389213233, "percentage": 19.63, "elapsed_time": "0:43:36", "remaining_time": "2:58:31"} | |
| {"current_steps": 540, "total_steps": 2700, "loss": 0.5668, "lr": 9.700670057343093e-06, "epoch": 0.6005004170141784, "percentage": 20.0, "elapsed_time": "0:44:25", "remaining_time": "2:57:41"} | |
| {"current_steps": 550, "total_steps": 2700, "loss": 0.581, "lr": 9.678247579197658e-06, "epoch": 0.6116207951070336, "percentage": 20.37, "elapsed_time": "0:45:14", "remaining_time": "2:56:51"} | |
| {"current_steps": 560, "total_steps": 2700, "loss": 0.5692, "lr": 9.655043177399236e-06, "epoch": 0.6227411731998888, "percentage": 20.74, "elapsed_time": "0:46:03", "remaining_time": "2:56:01"} | |
| {"current_steps": 570, "total_steps": 2700, "loss": 0.5778, "lr": 9.63106073033825e-06, "epoch": 0.6338615512927439, "percentage": 21.11, "elapsed_time": "0:46:53", "remaining_time": "2:55:12"} | |
| {"current_steps": 580, "total_steps": 2700, "loss": 0.5822, "lr": 9.60630424644784e-06, "epoch": 0.6449819293855991, "percentage": 21.48, "elapsed_time": "0:47:42", "remaining_time": "2:54:22"} | |
| {"current_steps": 590, "total_steps": 2700, "loss": 0.5885, "lr": 9.58077786353388e-06, "epoch": 0.6561023074784542, "percentage": 21.85, "elapsed_time": "0:48:31", "remaining_time": "2:53:33"} | |
| {"current_steps": 600, "total_steps": 2700, "loss": 0.5611, "lr": 9.554485848083389e-06, "epoch": 0.6672226855713094, "percentage": 22.22, "elapsed_time": "0:49:20", "remaining_time": "2:52:43"} | |
| {"current_steps": 610, "total_steps": 2700, "loss": 0.5586, "lr": 9.52743259455143e-06, "epoch": 0.6783430636641646, "percentage": 22.59, "elapsed_time": "0:50:10", "remaining_time": "2:51:53"} | |
| {"current_steps": 620, "total_steps": 2700, "loss": 0.5877, "lr": 9.499622624626624e-06, "epoch": 0.6894634417570198, "percentage": 22.96, "elapsed_time": "0:50:59", "remaining_time": "2:51:04"} | |
| {"current_steps": 630, "total_steps": 2700, "loss": 0.5768, "lr": 9.471060586475383e-06, "epoch": 0.700583819849875, "percentage": 23.33, "elapsed_time": "0:51:48", "remaining_time": "2:50:14"} | |
| {"current_steps": 640, "total_steps": 2700, "loss": 0.5612, "lr": 9.441751253965022e-06, "epoch": 0.7117041979427301, "percentage": 23.7, "elapsed_time": "0:52:38", "remaining_time": "2:49:26"} | |
| {"current_steps": 650, "total_steps": 2700, "loss": 0.5774, "lr": 9.411699525865849e-06, "epoch": 0.7228245760355853, "percentage": 24.07, "elapsed_time": "0:53:27", "remaining_time": "2:48:36"} | |
| {"current_steps": 660, "total_steps": 2700, "loss": 0.5908, "lr": 9.38091042503239e-06, "epoch": 0.7339449541284404, "percentage": 24.44, "elapsed_time": "0:54:17", "remaining_time": "2:47:47"} | |
| {"current_steps": 670, "total_steps": 2700, "loss": 0.5975, "lr": 9.349389097563858e-06, "epoch": 0.7450653322212956, "percentage": 24.81, "elapsed_time": "0:55:06", "remaining_time": "2:46:57"} | |
| {"current_steps": 680, "total_steps": 2700, "loss": 0.583, "lr": 9.31714081194404e-06, "epoch": 0.7561857103141507, "percentage": 25.19, "elapsed_time": "0:55:55", "remaining_time": "2:46:07"} | |
| {"current_steps": 690, "total_steps": 2700, "loss": 0.5724, "lr": 9.28417095816072e-06, "epoch": 0.7673060884070059, "percentage": 25.56, "elapsed_time": "0:56:44", "remaining_time": "2:45:16"} | |
| {"current_steps": 700, "total_steps": 2700, "loss": 0.5714, "lr": 9.25048504680479e-06, "epoch": 0.778426466499861, "percentage": 25.93, "elapsed_time": "0:57:33", "remaining_time": "2:44:26"} | |
| {"current_steps": 710, "total_steps": 2700, "loss": 0.567, "lr": 9.216088708149216e-06, "epoch": 0.7895468445927162, "percentage": 26.3, "elapsed_time": "0:58:22", "remaining_time": "2:43:35"} | |
| {"current_steps": 720, "total_steps": 2700, "loss": 0.5719, "lr": 9.18098769120798e-06, "epoch": 0.8006672226855713, "percentage": 26.67, "elapsed_time": "0:59:11", "remaining_time": "2:42:46"} | |
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