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README.md

@@ -220,10 +220,6 @@ chart understanding, complex table parsing, and document KVP extraction, supplem
 by the general-purpose Granite Vision instruction-following dataset
 ([arXiv:2502.09927](https://arxiv.org/abs/2502.09927)) for broad visual understanding.
 
-Chart understanding data was created through a novel code‑guided augmentation methodology that produces diverse, 
-semantically aligned chart samples containing rendering code, chart images, underlying data CSVs, and natural‑language summaries. 
-Using this pipeline, we are also releasing ChartNet (link TBD), a comprehensive million‑scale multimodal dataset enriched with real‑world, 
-human‑annotated, safety, and grounding subsets. The dataset and its methodology are detailed in our CVPR 2026 paper (link TBD).
 
 ## Model Architecture
 

adapter_config.json

@@ -21,17 +21,7 @@
   "lora_dropout": 0.05,
   "megatron_config": null,
   "megatron_core": "megatron.core",
-  "modules_to_save": [
-    "model.layerwise_projectors.0",
-    "model.layerwise_projectors.1",
-    "model.layerwise_projectors.2",
-    "model.layerwise_projectors.3",
-    "model.spatial_projectors.0",
-    "model.spatial_projectors.1",
-    "model.spatial_projectors.2",
-    "model.spatial_projectors.3",
-    "model.image_newline"
-  ],
+  "modules_to_save": null,
   "peft_type": "LORA",
   "qalora_group_size": 16,
   "r": 256,

adapter_model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:44cf3f332b387ca243c906304b03ab98edd78c4e0f2fa0db6662825d5dd35ede
-size 1276060048
+oid sha256:fbdb5a2c20dff4b7d79c8a877f1e55b73fdc6a5634e07af4c18aedcb80aa1d2d
+size 943793240