Image-Text-to-Text
Transformers
Safetensors
English
qwen3_5
qwen
qwen3.5
multimodal
vlm
continued-pretraining
cpt
repair
depth-upscaling
base-model
conversational
Instructions to use artivus-ai/qwen-3.5-80b-post-cpt-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use artivus-ai/qwen-3.5-80b-post-cpt-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="artivus-ai/qwen-3.5-80b-post-cpt-base") 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("artivus-ai/qwen-3.5-80b-post-cpt-base") model = AutoModelForMultimodalLM.from_pretrained("artivus-ai/qwen-3.5-80b-post-cpt-base", 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=40) print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use artivus-ai/qwen-3.5-80b-post-cpt-base with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "artivus-ai/qwen-3.5-80b-post-cpt-base" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "artivus-ai/qwen-3.5-80b-post-cpt-base", "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/artivus-ai/qwen-3.5-80b-post-cpt-base
- SGLang
How to use artivus-ai/qwen-3.5-80b-post-cpt-base 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 "artivus-ai/qwen-3.5-80b-post-cpt-base" \ --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": "artivus-ai/qwen-3.5-80b-post-cpt-base", "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 "artivus-ai/qwen-3.5-80b-post-cpt-base" \ --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": "artivus-ai/qwen-3.5-80b-post-cpt-base", "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 artivus-ai/qwen-3.5-80b-post-cpt-base with Docker Model Runner:
docker model run hf.co/artivus-ai/qwen-3.5-80b-post-cpt-base
Download trainer_state.json from artivus-ai/qwen-3.5-80b-post-cpt-base: direct link, hf CLI and curl.
- Browser
- Download file 5.14 kB
-
https://huggingface.co/artivus-ai/qwen-3.5-80b-post-cpt-base/resolve/main/trainer_state.json
- Command line
-
hf download hf://artivus-ai/qwen-3.5-80b-post-cpt-base/trainer_state.json
-
curl -L -o trainer_state.json https://huggingface.co/artivus-ai/qwen-3.5-80b-post-cpt-base/resolve/main/trainer_state.json
5.14 kB
| { | |
| "best_global_step": null, | |
| "best_metric": null, | |
| "best_model_checkpoint": null, | |
| "epoch": 0.1, | |
| "eval_steps": 100.0, | |
| "global_step": 100, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "epoch": 0.001, | |
| "grad_norm": 43.548129517838454, | |
| "learning_rate": 1.0000000000000002e-06, | |
| "loss": 4.1920576095581055, | |
| "step": 1, | |
| "token_acc": 0.34359059658460855 | |
| }, | |
| { | |
| "epoch": 0.005, | |
| "grad_norm": 14.427483007671363, | |
| "learning_rate": 5e-06, | |
| "loss": 2.9412002563476562, | |
| "step": 5, | |
| "token_acc": 0.512452240845581 | |
| }, | |
| { | |
| "epoch": 0.01, | |
| "grad_norm": 7.934074490008561, | |
| "learning_rate": 1e-05, | |
| "loss": 2.503311347961426, | |
| "step": 10, | |
| "token_acc": 0.5123253736192332 | |
| }, | |
| { | |
| "epoch": 0.015, | |
| "grad_norm": 2.5682097340060643, | |
| "learning_rate": 9.999370638369377e-06, | |
| "loss": 1.8719802856445313, | |
| "step": 15, | |
| "token_acc": 0.6410698878343399 | |
| }, | |
| { | |
| "epoch": 0.02, | |
| "grad_norm": 3.0601891911453225, | |
| "learning_rate": 9.997482711915926e-06, | |
| "loss": 1.7852279663085937, | |
| "step": 20, | |
| "token_acc": 0.6242933840865835 | |
| }, | |
| { | |
| "epoch": 0.025, | |
| "grad_norm": 2.9591215037175895, | |
| "learning_rate": 9.994336695915041e-06, | |
| "loss": 1.6610099792480468, | |
| "step": 25, | |
| "token_acc": 0.6568298460323727 | |
| }, | |
| { | |
| "epoch": 0.03, | |
| "grad_norm": 2.3839735362461623, | |
| "learning_rate": 9.989933382359423e-06, | |
| "loss": 1.6115425109863282, | |
| "step": 30, | |
| "token_acc": 0.6632120451693851 | |
| }, | |
| { | |
| "epoch": 0.035, | |
| "grad_norm": 2.0296518100505776, | |
| "learning_rate": 9.984273879759713e-06, | |
| "loss": 1.7307615280151367, | |
| "step": 35, | |
| "token_acc": 0.6267176116002563 | |
| }, | |
| { | |
| "epoch": 0.04, | |
| "grad_norm": 2.274063193212189, | |
| "learning_rate": 9.977359612865424e-06, | |
| "loss": 1.6226930618286133, | |
| "step": 40, | |
| "token_acc": 0.6632471264367816 | |
| }, | |
| { | |
| "epoch": 0.045, | |
| "grad_norm": 1.995496122888669, | |
| "learning_rate": 9.969192322306271e-06, | |
| "loss": 1.6562419891357423, | |
| "step": 45, | |
| "token_acc": 0.6479170419164758 | |
| }, | |
| { | |
| "epoch": 0.05, | |
| "grad_norm": 2.030243788478171, | |
| "learning_rate": 9.959774064153977e-06, | |
| "loss": 1.5927490234375, | |
| "step": 50, | |
| "token_acc": 0.6578526695879487 | |
| }, | |
| { | |
| "epoch": 0.055, | |
| "grad_norm": 1.913105067952688, | |
| "learning_rate": 9.949107209404664e-06, | |
| "loss": 1.886464500427246, | |
| "step": 55, | |
| "token_acc": 0.5819125113628805 | |
| }, | |
| { | |
| "epoch": 0.06, | |
| "grad_norm": 1.8949380801330526, | |
| "learning_rate": 9.937194443381972e-06, | |
| "loss": 1.6359737396240235, | |
| "step": 60, | |
| "token_acc": 0.6552567735622108 | |
| }, | |
| { | |
| "epoch": 0.065, | |
| "grad_norm": 1.4853873443995649, | |
| "learning_rate": 9.924038765061042e-06, | |
| "loss": 1.3352900505065919, | |
| "step": 65, | |
| "token_acc": 0.7206670637284097 | |
| }, | |
| { | |
| "epoch": 0.07, | |
| "grad_norm": 1.6844968929576292, | |
| "learning_rate": 9.909643486313533e-06, | |
| "loss": 1.4845345497131348, | |
| "step": 70, | |
| "token_acc": 0.6865343744776369 | |
| }, | |
| { | |
| "epoch": 0.075, | |
| "grad_norm": 1.7982742317399707, | |
| "learning_rate": 9.894012231073895e-06, | |
| "loss": 1.5165021896362305, | |
| "step": 75, | |
| "token_acc": 0.6689946239260413 | |
| }, | |
| { | |
| "epoch": 0.08, | |
| "grad_norm": 1.7083434381167786, | |
| "learning_rate": 9.877148934427037e-06, | |
| "loss": 1.501682949066162, | |
| "step": 80, | |
| "token_acc": 0.6582693568920952 | |
| }, | |
| { | |
| "epoch": 0.085, | |
| "grad_norm": 2.276089893387222, | |
| "learning_rate": 9.859057841617709e-06, | |
| "loss": 1.3892568588256835, | |
| "step": 85, | |
| "token_acc": 0.7173441424982873 | |
| }, | |
| { | |
| "epoch": 0.09, | |
| "grad_norm": 3.2510132262305955, | |
| "learning_rate": 9.839743506981783e-06, | |
| "loss": 1.6044925689697265, | |
| "step": 90, | |
| "token_acc": 0.6260809087747768 | |
| }, | |
| { | |
| "epoch": 0.095, | |
| "grad_norm": 2.3567789267765544, | |
| "learning_rate": 9.819210792799711e-06, | |
| "loss": 1.531374168395996, | |
| "step": 95, | |
| "token_acc": 0.661787561762045 | |
| }, | |
| { | |
| "epoch": 0.1, | |
| "grad_norm": 1.7140659626033266, | |
| "learning_rate": 9.797464868072489e-06, | |
| "loss": 1.636698341369629, | |
| "step": 100, | |
| "token_acc": 0.6505466960542806 | |
| } | |
| ], | |
| "logging_steps": 5, | |
| "max_steps": 1000, | |
| "num_input_tokens_seen": 0, | |
| "num_train_epochs": 9223372036854775807, | |
| "save_steps": 100, | |
| "stateful_callbacks": { | |
| "TrainerControl": { | |
| "args": { | |
| "should_epoch_stop": false, | |
| "should_evaluate": false, | |
| "should_log": false, | |
| "should_save": true, | |
| "should_training_stop": false | |
| }, | |
| "attributes": {} | |
| } | |
| }, | |
| "total_flos": 93095931019264.0, | |
| "train_batch_size": 1, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |