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License
apache-2.0
Tasks
image-text-to-text
Frameworks
transformers
Hardware-aware snippets
Runtime-specific quick starts for unsloth/Qwen2.5-VL-7B-Instruct-unsloth-bnb-4bit. Detected hardware: No explicit hardware metadata.
Task: image-text-to-textTransformers
NVIDIA CUDA path
Best default for NVIDIA GPUs and hosted accelerator nodes.
pip install torch transformers accelerate
python - <<'PY'
from transformers import pipeline
model_id = "unsloth/Qwen2.5-VL-7B-Instruct-unsloth-bnb-4bit"
pipe = pipeline(
task="image-text-to-text",
model=model_id,
device_map="auto",
model_kwargs={"torch_dtype": "auto"},
)
print(pipe("Hello from Inferix"))
PYModel lineage
1 reposBase model
Qwen/Qwen2.5-VL-7B-InstructFinetuned
1Qwen2.5-VL-7B-Instruct-unsloth-bnb-4bitselected
Quantizations
0No quantization variants detected.
Model info
Namespace
unsloth
Visibility
public
Downloads
1
Likes
0
License: apache-2.0
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Metadata links
Base model
Qwen/Qwen2.5-VL-7B-InstructTrained on datasets
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Linked papers
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Inference providers
0/0 fitNot available for inference yet.
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Tags
importedhuggingfaceminiotransformerssafetensorsqwen2_5_vlimage-text-to-textmultimodalunslothconversationalenarxiv:2309.00071arxiv:2409.12191arxiv:2308.12966base_model:Qwen/Qwen2.5-VL-7B-Instructbase_model:quantized:Qwen/Qwen2.5-VL-7B-Instructlicense:apache-2.0text-generation-inferenceendpoints_compatible4-bitbitsandbytesdeploy:azureregion:us