Upload nanoVLM using push_to_hub

README.md

@@ -0,0 +1,27 @@
+
+---
+# For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1
+# Doc / guide: https://huggingface.co/docs/hub/model-cards
+library_name: nanovlm
+license: mit
+pipeline_tag: image-text-to-text
+tags:
+  - vision-language
+  - multimodal
+  - research
+---
+
+**nanoVLM** is a minimal and lightweight Vision-Language Model (VLM) designed for efficient training and experimentation. Built using pure PyTorch, the entire model architecture and training logic fits within ~750 lines of code. It combines a ViT-based image encoder (SigLIP-B/16-224-85M) with a lightweight causal language model (SmolLM2-135M), resulting in a compact 222M parameter model.
+
+For more information, check out the base model on https://huggingface.co/lusxvr/nanoVLM-222M.
+
+**Usage:**
+
+Clone the nanoVLM repository: https://github.com/huggingface/nanoVLM.
+Follow the install instructions and run the following code:
+
+```python
+from models.vision_language_model import VisionLanguageModel
+
+model = VisionLanguageModel.from_pretrained("zhili-zh/nanoVLM")
+```

config.json

@@ -0,0 +1,56 @@
+{
+    "vit_hidden_dim": 768,
+    "vit_inter_dim": 3072,
+    "vit_patch_size": 16,
+    "vit_img_size": 512,
+    "vit_n_heads": 12,
+    "vit_dropout": 0.0,
+    "vit_n_blocks": 12,
+    "vit_ln_eps": 1e-06,
+    "vit_cls_flag": false,
+    "vit_model_type": "google/siglip2-base-patch16-512",
+    "lm_hidden_dim": 960,
+    "lm_inter_dim": 2560,
+    "lm_rms_eps": 1e-05,
+    "lm_re_base": 100000,
+    "lm_max_position_embeddings": 8192,
+    "lm_base_vocab_size": 49152,
+    "extra_token_amount": 17,
+    "lm_vocab_size": 49169,
+    "lm_n_heads": 15,
+    "lm_n_kv_heads": 5,
+    "lm_dropout": 0.0,
+    "lm_n_blocks": 32,
+    "lm_attn_scaling": 1.0,
+    "lm_max_length": 1024,
+    "lm_use_tokens": false,
+    "lm_tie_weights": true,
+    "lm_model_type": "HuggingFaceTB/SmolLM2-360M-Instruct",
+    "lm_tokenizer": "HuggingFaceTB/SmolLM2-360M-Instruct",
+    "lm_chat_template": "{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
+    "mp_pixel_shuffle_factor": 4,
+    "mp_image_token_length": 64,
+    "max_img_size": 1024,
+    "vlm_extra_tokens": {
+        "image_token": "<|image|>",
+        "r1c1": "<row_1_col_1>",
+        "r1c2": "<row_1_col_2>",
+        "r1c3": "<row_1_col_3>",
+        "r1c4": "<row_1_col_4>",
+        "r2c1": "<row_2_col_1>",
+        "r2c2": "<row_2_col_2>",
+        "r2c3": "<row_2_col_3>",
+        "r2c4": "<row_2_col_4>",
+        "r3c1": "<row_3_col_1>",
+        "r3c2": "<row_3_col_2>",
+        "r3c3": "<row_3_col_3>",
+        "r3c4": "<row_3_col_4>",
+        "r4c1": "<row_4_col_1>",
+        "r4c2": "<row_4_col_2>",
+        "r4c3": "<row_4_col_3>",
+        "r4c4": "<row_4_col_4>"
+    },
+    "vlm_load_backbone_weights": true,
+    "vlm_checkpoint_path": "checkpoints",
+    "hf_repo_name": "nanoVLM"
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7d7d68128c84e6e8f54537a1bc8edbc8830b16e3f3be3730184cc259e20729c5
+size 1840316344