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README.md

@@ -6,6 +6,7 @@ tags:
 - unsloth
 - paddleocr_vl
 - trl
+- sft
 license: apache-2.0
 language:
 - en

config.json

@@ -0,0 +1,78 @@
+{
+  "architectures": [
+    "PaddleOCRVLForConditionalGeneration"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "auto_map": {
+    "AutoConfig": "configuration_paddleocr_vl.PaddleOCRVLConfig",
+    "AutoModel": "modeling_paddleocr_vl.PaddleOCRVLForConditionalGeneration",
+    "AutoModelForCausalLM": "modeling_paddleocr_vl.PaddleOCRVLForConditionalGeneration"
+  },
+  "bos_token_id": 1,
+  "compression_ratio": 1.0,
+  "dtype": "float32",
+  "eos_token_id": 2,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 1024,
+  "ignored_index": -100,
+  "image_token_id": 100295,
+  "intermediate_size": 3072,
+  "max_position_embeddings": 131072,
+  "max_sequence_length": null,
+  "model_type": "paddleocr_vl",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 18,
+  "num_key_value_heads": 2,
+  "pad_token_id": 0,
+  "rms_norm_eps": 1e-05,
+  "rope_is_neox_style": true,
+  "rope_scaling": {
+    "mrope_section": [
+      16,
+      24,
+      24
+    ],
+    "rope_type": "default",
+    "type": "default"
+  },
+  "rope_theta": 500000,
+  "sliding_window": null,
+  "tie_word_embeddings": false,
+  "transformers_version": "4.56.2",
+  "unsloth_version": "2025.12.8",
+  "use_3d_rope": true,
+  "use_bias": false,
+  "use_cache": false,
+  "use_flash_attention": false,
+  "video_token_id": 101307,
+  "vision_config": {
+    "architectures": [
+      "PaddleOCRVisionModel"
+    ],
+    "attention_dropout": 0.0,
+    "auto_map": {
+      "AutoConfig": "configuration_paddleocr_vl.PaddleOCRVLConfig",
+      "AutoModel": "modeling_paddleocr_vl.PaddleOCRVisionModel"
+    },
+    "dtype": "float16",
+    "hidden_act": "gelu_pytorch_tanh",
+    "hidden_size": 1152,
+    "image_size": 384,
+    "intermediate_size": 4304,
+    "layer_norm_eps": 1e-06,
+    "model_type": "paddleocr_vl",
+    "num_attention_heads": 16,
+    "num_channels": 3,
+    "num_hidden_layers": 27,
+    "pad_token_id": 0,
+    "patch_size": 14,
+    "spatial_merge_size": 2,
+    "temporal_patch_size": 2,
+    "tokens_per_second": 2
+  },
+  "vision_start_token_id": 101305,
+  "vocab_size": 103424,
+  "weight_share_add_bias": true
+}

configuration_paddleocr_vl.py

@@ -0,0 +1,191 @@
+# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from transformers.configuration_utils import PretrainedConfig
+from transformers.modeling_rope_utils import rope_config_validation
+
+class PaddleOCRVisionConfig(PretrainedConfig):
+    model_type = "paddleocr_vl"
+    base_config_key = "vision_config"
+
+    def __init__(
+        self,
+        hidden_size=768,
+        intermediate_size=3072,
+        num_hidden_layers=12,
+        num_attention_heads=12,
+        num_channels=3,
+        image_size=224,
+        patch_size=14,
+        hidden_act="gelu_pytorch_tanh",
+        layer_norm_eps=1e-6,
+        attention_dropout=0.0,
+        spatial_merge_size=2,
+        temporal_patch_size=2,
+        tokens_per_second=2,
+        **kwargs,
+    ):
+        super().__init__(**kwargs)
+
+        self.hidden_size = hidden_size
+        self.intermediate_size = intermediate_size
+        self.num_hidden_layers = num_hidden_layers
+        self.num_attention_heads = num_attention_heads
+        self.num_channels = num_channels
+        self.patch_size = patch_size
+        self.image_size = image_size
+        self.attention_dropout = attention_dropout
+        self.layer_norm_eps = layer_norm_eps
+        self.hidden_act = hidden_act
+        self.spatial_merge_size = spatial_merge_size
+        self.temporal_patch_size = temporal_patch_size
+        self.tokens_per_second = tokens_per_second
+
+
+
+class PaddleOCRVLConfig(PretrainedConfig):
+    """
+    Configuration class.
+
+    This class stores the configuration of an Ernie model, defining the model architecture.
+    It inherits from PretrainedConfig and can be used to control model outputs.
+    """
+
+    model_type = "paddleocr_vl"
+    keys_to_ignore_at_inference = ["past_key_values"]
+    sub_configs = {"vision_config": PaddleOCRVisionConfig}
+
+    # Default tensor parallel plan for base model `Qwen3`
+    base_model_tp_plan = {
+        "layers.*.self_attn.q_proj": "colwise",
+        "layers.*.self_attn.k_proj": "colwise",
+        "layers.*.self_attn.v_proj": "colwise",
+        "layers.*.self_attn.o_proj": "rowwise",
+        "layers.*.mlp.gate_proj": "colwise",
+        "layers.*.mlp.up_proj": "colwise",
+        "layers.*.mlp.down_proj": "rowwise",
+    }
+    base_model_pp_plan = {
+        "embed_tokens": (["input_ids"], ["inputs_embeds"]),
+        "layers": (["hidden_states", "attention_mask"], ["hidden_states"]),
+        "norm": (["hidden_states"], ["hidden_states"]),
+    }
+
+    def __init__(
+        self,
+        vocab_size=32000,
+        hidden_size=768,
+        intermediate_size=11008,
+        max_position_embeddings=32768,
+        num_hidden_layers=2,
+        num_attention_heads=2,
+        image_token_id=101304,
+        video_token_id=101305,
+        vision_start_token_id=101306,
+        rms_norm_eps=1e-6,
+        use_cache=False,
+        use_flash_attention=False,
+        pad_token_id=0,
+        bos_token_id=1,
+        eos_token_id=2,
+        head_dim=128,
+        hidden_act="silu",
+        use_bias=False,
+        rope_theta=10000,
+        weight_share_add_bias=True,
+        ignored_index=-100,
+        attention_probs_dropout_prob=0.0,
+        hidden_dropout_prob=0.0,
+        compression_ratio: float = 1.0,
+        num_key_value_heads=None,
+        max_sequence_length=None,
+        tie_word_embeddings=False,
+        vision_config=None,
+        rope_scaling=None,
+        **kwargs,
+    ):
+        """
+        Initialize configuration with default or specified parameters.
+
+        Args:
+            vocab_size (int): Size of the vocabulary (number of unique tokens)
+            hidden_size (int): Dimensionality of the encoder layers and the pooler layer
+            intermediate_size (int): Dimensionality of the "intermediate" (feed-forward) layer
+            max_position_embeddings (int): Maximum sequence length the model can handle
+            num_hidden_layers (int): Number of hidden layers in the Transformer encoder
+            num_attention_heads (int): Number of attention heads for each attention layer
+            rms_norm_eps (float): The epsilon used by the RMS normalization layers
+            use_cache (bool): Whether to use caching for faster generation (decoding)
+            use_flash_attention (bool): Whether to use FlashAttention for optimized attention computation
+            pad_token_id (int): Token ID used for padding sequences
+            bos_token_id (int): Token ID used for beginning-of-sequence
+            eos_token_id (int): Token ID used for end-of-sequence
+            use_bias (bool): Whether to use bias terms in linear layers
+            rope_theta (float): The base period of the RoPE embeddings
+            weight_share_add_bias (bool): Whether to share bias weights in certain layers
+            ignored_index (int): Target value that is ignored during loss computation
+            attention_probs_dropout_prob (float): Dropout probability for attention weights
+            hidden_dropout_prob (float): Dropout probability for hidden layers
+            compression_ratio (float): Ratio for KV cache compression (1.0 = no compression)
+            num_key_value_heads (int): Number of key/value heads (for Grouped Query Attention)
+            max_sequence_length (int): Maximum sequence length for positional embeddings
+            **kwargs: Additional keyword arguments passed to parent class
+        """
+
+        # Set default for tied embeddings if not specified.
+        super().__init__(
+            pad_token_id=pad_token_id,
+            bos_token_id=bos_token_id,
+            eos_token_id=eos_token_id,
+            **kwargs,
+        )
+        if isinstance(vision_config, dict):
+            self.vision_config = self.sub_configs["vision_config"](**vision_config)
+        elif vision_config is None:
+            self.vision_config = self.sub_configs["vision_config"]()        
+        self.vocab_size = vocab_size
+        self.hidden_size = hidden_size
+        self.intermediate_size = intermediate_size
+        self.max_position_embeddings = max_position_embeddings
+        self.num_hidden_layers = num_hidden_layers
+        self.num_attention_heads = num_attention_heads
+        self.rms_norm_eps = rms_norm_eps
+        self.use_cache = use_cache
+        self.use_flash_attention = use_flash_attention
+        self.pad_token_id = pad_token_id
+        self.bos_token_id = bos_token_id
+        self.eos_token_id = eos_token_id
+        self.image_token_id = image_token_id
+        self.video_token_id = video_token_id
+        self.vision_start_token_id = vision_start_token_id
+        self.head_dim = head_dim
+        self.hidden_act=hidden_act
+        self.sliding_window = None
+        self.hidden_size = hidden_size
+        self.use_bias = use_bias
+        self.weight_share_add_bias = weight_share_add_bias
+        self.rope_theta = rope_theta
+        self.ignored_index = ignored_index
+        self.attention_probs_dropout_prob = attention_probs_dropout_prob
+        self.hidden_dropout_prob = hidden_dropout_prob
+        self.compression_ratio = compression_ratio
+        self.num_key_value_heads = num_key_value_heads
+        self.max_sequence_length = max_sequence_length
+        self.rope_scaling = rope_scaling
+        if self.rope_scaling is not None and "type" in self.rope_scaling:
+            if self.rope_scaling["type"] == "mrope":
+                self.rope_scaling["type"] = "default"
+            self.rope_scaling["rope_type"] = self.rope_scaling["type"]
+        rope_config_validation(self, ignore_keys={"mrope_section"})        
+        super().__init__(tie_word_embeddings=tie_word_embeddings, **kwargs)

generation_config.json

@@ -0,0 +1,12 @@
+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": [
+    2,
+    2
+  ],
+  "max_length": 131072,
+  "pad_token_id": 0,
+  "transformers_version": "4.56.2",
+  "use_cache": false
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:305b9e13a0fdbd3201db363da4cabda0f0311d1533c45e8b7ea79bb6ae715d02
+size 3826461296