Instructions to use chancharikm/dpo_all_20251113_ep5_lr5e6_qwen3-vl-8b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use chancharikm/dpo_all_20251113_ep5_lr5e6_qwen3-vl-8b with PEFT:

from peft import PeftModel
from transformers import AutoModelForCausalLM

base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-VL-8B-Instruct")
model = PeftModel.from_pretrained(base_model, "chancharikm/dpo_all_20251113_ep5_lr5e6_qwen3-vl-8b")

Transformers

How to use chancharikm/dpo_all_20251113_ep5_lr5e6_qwen3-vl-8b with Transformers:

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

pipe = pipeline("text-generation", model="chancharikm/dpo_all_20251113_ep5_lr5e6_qwen3-vl-8b")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("chancharikm/dpo_all_20251113_ep5_lr5e6_qwen3-vl-8b", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use chancharikm/dpo_all_20251113_ep5_lr5e6_qwen3-vl-8b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "chancharikm/dpo_all_20251113_ep5_lr5e6_qwen3-vl-8b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "chancharikm/dpo_all_20251113_ep5_lr5e6_qwen3-vl-8b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/chancharikm/dpo_all_20251113_ep5_lr5e6_qwen3-vl-8b

SGLang

How to use chancharikm/dpo_all_20251113_ep5_lr5e6_qwen3-vl-8b 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 "chancharikm/dpo_all_20251113_ep5_lr5e6_qwen3-vl-8b" \
    --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": "chancharikm/dpo_all_20251113_ep5_lr5e6_qwen3-vl-8b",
		"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 "chancharikm/dpo_all_20251113_ep5_lr5e6_qwen3-vl-8b" \
        --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": "chancharikm/dpo_all_20251113_ep5_lr5e6_qwen3-vl-8b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use chancharikm/dpo_all_20251113_ep5_lr5e6_qwen3-vl-8b with Docker Model Runner:
```
docker model run hf.co/chancharikm/dpo_all_20251113_ep5_lr5e6_qwen3-vl-8b
```

chancharikm commited on Nov 16, 2025

Commit

7cd06de

verified ·

1 Parent(s): c795e14

Model save

Browse files

Files changed (3) hide show

README.md +64 -0
preprocessor_config.json +39 -0
video_preprocessor_config.json +41 -0

README.md ADDED Viewed

	@@ -0,0 +1,64 @@

+---
+library_name: peft
+license: apache-2.0
+base_model: Qwen/Qwen3-VL-8B-Instruct
+tags:
+- base_model:adapter:Qwen/Qwen3-VL-8B-Instruct
+- llama-factory
+- lora
+- transformers
+pipeline_tag: text-generation
+model-index:
+- name: dpo_all_20251113_ep5_lr5e6_qwen3-vl-8b
+  results: []
+---
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+# dpo_all_20251113_ep5_lr5e6_qwen3-vl-8b
+This model is a fine-tuned version of [Qwen/Qwen3-VL-8B-Instruct](https://huggingface.co/Qwen/Qwen3-VL-8B-Instruct) on an unknown dataset.
+## Model description
+More information needed
+## Intended uses & limitations
+More information needed
+## Training and evaluation data
+More information needed
+## Training procedure
+### Training hyperparameters
+The following hyperparameters were used during training:
+- learning_rate: 1e-05
+- train_batch_size: 4
+- eval_batch_size: 8
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 64
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 2048
+- total_eval_batch_size: 512
+- optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 3.0
+### Training results
+### Framework versions
+- PEFT 0.17.1
+- Transformers 4.57.1
+- Pytorch 2.9.1+cu128
+- Datasets 4.0.0
+- Tokenizers 0.22.1

preprocessor_config.json ADDED Viewed

	@@ -0,0 +1,39 @@

+{
+  "crop_size": null,
+  "data_format": "channels_first",
+  "default_to_square": true,
+  "device": null,
+  "disable_grouping": null,
+  "do_center_crop": null,
+  "do_convert_rgb": true,
+  "do_normalize": true,
+  "do_pad": null,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "image_processor_type": "Qwen2VLImageProcessorFast",
+  "image_std": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "input_data_format": null,
+  "max_pixels": null,
+  "merge_size": 2,
+  "min_pixels": null,
+  "pad_size": null,
+  "patch_size": 16,
+  "processor_class": "Qwen3VLProcessor",
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "return_tensors": null,
+  "size": {
+    "longest_edge": 16777216,
+    "shortest_edge": 65536
+  },
+  "temporal_patch_size": 2
+}

video_preprocessor_config.json ADDED Viewed

	@@ -0,0 +1,41 @@

+{
+  "crop_size": null,
+  "data_format": "channels_first",
+  "default_to_square": true,
+  "device": null,
+  "do_center_crop": null,
+  "do_convert_rgb": true,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "do_sample_frames": true,
+  "fps": 2,
+  "image_mean": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "image_std": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "input_data_format": null,
+  "max_frames": 768,
+  "merge_size": 2,
+  "min_frames": 4,
+  "num_frames": null,
+  "pad_size": null,
+  "patch_size": 16,
+  "processor_class": "Qwen3VLProcessor",
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "return_metadata": false,
+  "size": {
+    "longest_edge": 25165824,
+    "shortest_edge": 4096
+  },
+  "temporal_patch_size": 2,
+  "video_metadata": null,
+  "video_processor_type": "Qwen3VLVideoProcessor"
+}