inintial commit

LICENSE

@@ -0,0 +1,22 @@
+MIT License
+
+Copyright (c) 2025 AIRAS
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
+

README.md

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+---
+license_name: mit
+language:
+- en
+pipeline_tag: image-text-to-text
+tags:
+- multimodal
+library_name: transformers
+base_model:
+- Sapnous/Sapnous-6B
+license: mit
+---
+
+![icon.png](https://cdn-uploads.huggingface.co/production/uploads/675d3ca88d0f15d76e49d5ea/YhcU9ACkEsJXPAgQZz1bX.png)
+
+
+# Sapnous-6B: A Vision-Language Model for Enhanced World Perception
+
+Sapnous-6B is a state-of-the-art vision-language model designed to enhance perception and understanding of the world through advanced multimodal capabilities. This model builds upon the success of previous vision-language architectures while introducing novel improvements in performance and efficiency.
+
+## Model Architecture
+
+- **Base Architecture**: 6B parameters
+- **Hidden Size**: 4096
+- **Attention Heads**: 32
+- **Key/Value Heads**: 8
+- **Hidden Layers**: 28
+- **Window Size**: 32768
+- **Vision Encoder**:
+  - Depth: 32 layers
+  - Hidden Size: 1280
+  - Attention Heads: 16
+  - Patch Size: 14x14
+  - Window Size: 112
+
+## Scores
+
+## **📊 Benchmark Results**  
+
+### **Multimodal Benchmarks**
+| Benchmark                  | InternVL2.5-8B | MiniCPM-o 2.6 | GPT-4o-mini | Qwen2-VL-7B | Qwen2.5-VL-7B | **Sapnous-MoE** | **Sapnous-6B** |
+|----------------------------|---------------|--------------|-------------|-------------|---------------|---------------|---------------|
+| MMMU_val                  | 56            | 50.4         | **60**      | 54.1        | 58.6          | **61.3**      | **60.2**      |
+| MMMU-Pro_val              | 34.3          | -            | 37.6        | 30.5        | 41.0          | **41.9**      | **40.7**      |
+| DocVQA_test               | 93            | 93           | -           | 94.5        | **95.7**      | **96.8**      | **95.6**      |
+| InfoVQA_test              | 77.6          | -            | -           | 76.5        | **82.6**      | **83.2**      | **81.9**      |
+| ChartQA_test              | 84.8          | -            | -           | 83.0        | **87.3**      | **88.5**      | **87.2**      |
+| TextVQA_val               | 79.1          | 80.1         | -           | 84.3        | **84.9**      | **85.8**      | **84.6**      |
+| OCRBench                  | 822           | 852          | 785         | 845         | **864**       | **872**       | **861**       |
+| CC_OCR                    | 57.7          | -            | -           | 61.6        | **77.8**      | **78.5**      | **77.3**      |
+| MMStar                    | 62.8          | -            | -           | 60.7        | **63.9**      | **64.9**      | **63.6**      |
+| MMBench-V1.1-En_test      | 79.4          | 78.0         | 76.0        | 80.7        | **82.6**      | **83.7**      | **82.4**      |
+| MMT-Bench_test            | -             | -            | -           | 63.7        | **63.6**      | **64.5**      | **63.3**      |
+| MMStar                    | **61.5**      | 57.5         | 54.8        | 60.7        | **63.9**      | **64.9**      | **63.6**      |
+| MMVet_GPT-4-Turbo         | 54.2          | 60.0         | 66.9        | 62.0        | **67.1**      | **68.5**      | **67.2**      |
+| HallBench_avg             | 45.2          | 48.1         | 46.1        | 50.6        | **52.9**      | **53.8**      | **52.5**      |
+| MathVista_testmini        | 58.3          | 60.6         | 52.4        | 58.2        | **68.2**      | **69.1**      | **67.9**      |
+| MathVision                | -             | -            | -           | 16.3        | **25.07**     | **25.9**      | **24.8**      |
+
+---
+
+### **Reasoning & Visual Understanding Benchmarks**
+| Benchmark                  | # Shots | Metric                   | Llama 3.2 11B | Llama 3.2 90B | **Sapnous-MoE** | **Sapnous-6B** |
+|----------------------------|---------|--------------------------|--------------|--------------|--------------|--------------|
+| VQAv2 (val)               | 0       | Accuracy                 | 66.8         | 73.6         | **75.3**     | **74.1**     |
+| Text VQA (val)            | 0       | Relaxed accuracy         | 73.1         | 73.5         | **75.9**     | **74.7**     |
+| DocVQA (val, unseen)      | 0       | ANLS                     | 62.3         | 70.7         | **72.1**     | **71.0**     |
+| MMMU (val, 0-shot)        | 0       | Micro average accuracy   | 41.7         | 49.3         | **50.4**     | **49.2**     |
+| ChartQA (test)            | 0       | Accuracy                 | 39.4         | 54.2         | **55.3**     | **54.1**     |
+| InfographicsQA (val, unseen) | 0    | ANLS                     | 43.2         | 56.8         | **58.3**     | **57.1**     |
+| AI2 Diagram (test)        | 0       | Accuracy                 | 62.4         | 75.3         | **76.9**     | **75.6**     |
+| MMMU (val, CoT)          | 0       | Micro average accuracy   | 50.7         | 60.3         | **61.9**     | **60.6**     |
+| MMMU-Pro, Standard (10 opts, test) | 0 | Accuracy               | 33.0         | 45.2         | **46.7**     | **45.5**     |
+| MMMU-Pro, Vision (test)   | 0       | Accuracy                 | 23.7         | 33.8         | **35.1**     | **33.9**     |
+| MathVista (testmini)      | 0       | Accuracy                 | 51.5         | 57.3         | **58.8**     | **57.5**     |
+| ChartQA (test, CoT)       | 0       | Relaxed accuracy         | 83.4         | 85.5         | **87.2**     | **86.0**     |
+| AI2 Diagram (test)        | 0       | Accuracy                 | 91.1         | 92.3         | **94.8**     | **93.5**     |
+| DocVQA (test)            | 0       | ANLS                     | 88.4         | 90.1         | **92.5**     | **91.3**     |
+| VQAv2 (test)             | 0       | Accuracy                 | 75.2         | 78.1         | **80.2**     | **79.0**     |
+| MMLU (CoT)               | 0       | Macro_avg/acc            | 73.0         | 86.0         | **88.2**     | **87.0**     |
+| MATH (CoT)               | 0       | Final_em                 | 51.9         | 68.0         | **69.7**     | **68.5**     |
+| GPQA                     | 0       | Accuracy                 | 32.8         | 46.7         | **47.9**     | **46.7**     |
+| MGSM (CoT)               | 0       | em                       | 68.9         | 86.9         | **88.7**     | **87.4**     |
+
+---
+
+## Model Structure
+
+The model is distributed across 5 safetensors files for efficient loading and memory management. Each file contains specific layers and weights as documented in the model.safetensors.index.json.
+
+## Usage
+
+```python
+from transformers import AutoProcessor, AutoModelForCausalLM
+
+# Load model and processor
+model = AutoModelForCausalLM.from_pretrained("path/to/Sapnous-6B")
+processor = AutoProcessor.from_pretrained("path/to/Sapnous-6B")
+
+# Prepare inputs
+inputs = processor(images=image, text=prompt, return_tensors="pt")
+
+# Generate
+generated_ids = model.generate(**inputs, max_new_tokens=128)
+generated_ids_trimmed = [out_ids[len(in_ids):] for in_ids, out_ids in 
+zip(inputs.input_ids, generated_ids)]
+output_text = processor.batch_decode(
+    generated_ids_trimmed,
+    skip_special_tokens=True,
+    clean_up_tokenization_spaces=False
+)
+```
+
+## Model Capabilities
+
+- Multi-modal understanding and generation
+- Enhanced visual perception with advanced vision encoder
+- Efficient processing of long sequences
+- Robust performance across various vision-language tasks
+
+## Citations
+
+```bibtex
+@misc{sapnous-6b,
+    title = {Sapnous-6B},
+    author = {Sapnous AI Team},
+    year = {2025}
+}
+
+@article{Sapnous6B,
+    title={Sapnous-6B: Enhancing Vision-Language Model's Perception of the World at Any Resolution},
+    author={Sapnous AI Team},
+    year={2025}
+}
+
+@article{Sapnous-VR,
+    title={Sapnous-VR: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond},
+    author={Sapnous AI Team},
+    year={2025}
+}
+```
+
+## License
+
+Please refer to the LICENSE file for terms of use and distribution.

__init__.py

@@ -0,0 +1,16 @@
+from .configuration_sapnous import SapnousConfig
+from .modeling_sapnous import SapnousModel
+from typing import TYPE_CHECKING
+from transformers.utils import _LazyModule
+
+_import_structure = {
+    "configuration_sapnous": ["SAPNOUS_PRETRAINED_CONFIG_ARCHIVE_MAP", "SapnousT1Config"],
+    "modeling_sapnous": ["SapnousT1Model", "SapnousT1ForCausalLM"],
+}
+
+if TYPE_CHECKING:
+    from .configuration_sapnous import SAPNOUS_PRETRAINED_CONFIG_ARCHIVE_MAP, SapnousT1Config
+    from .modeling_sapnous import SapnousT1Model, SapnousT1ForCausalLM
+else:
+    import sys
+    sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure)

chat_template.json

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+{
+    "chat_template": "{% set image_count = namespace(value=0) %}{% set video_count = namespace(value=0) %}{% for message in messages %}{% if loop.first and message['role'] != 'system' %}<|im_start|>system\nYou are a Sapnous by AIRAS.<|im_end|>\n{% endif %}<|im_start|>{{ message['role'] }}\n{% if message['content'] is string %}{{ message['content'] }}<|im_end|>\n{% else %}{% for content in message['content'] %}{% if content['type'] == 'image' or 'image' in content or 'image_url' in content %}{% set image_count.value = image_count.value + 1 %}{% if add_vision_id %}Picture {{ image_count.value }}: {% endif %}<|vision_start|><|image_pad|><|vision_end|>{% elif content['type'] == 'video' or 'video' in content %}{% set video_count.value = video_count.value + 1 %}{% if add_vision_id %}Video {{ video_count.value }}: {% endif %}<|vision_start|><|video_pad|><|vision_end|>{% elif 'text' in content %}{{ content['text'] }}{% endif %}{% endfor %}<|im_end|>\n{% endif %}{% endfor %}{% if add_generation_prompt %}<|im_start|>assistant\n{% endif %}"
+}

config.json

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+{
+  "architectures": [
+    "SapnousT1ForCausalLM"
+  ],
+  "auto_map": {
+    "AutoConfig": "configuration_sapnous.SapnousT1Config",
+    "AutoModel": "modeling_sapnous.SapnousT1Model",
+    "AutoModelForCausalLM": "modeling_sapnous.SapnousT1ForCausalLM"
+  },
+  "attention_dropout": 0.0,
+  "bos_token_id": 151643,
+  "eos_token_id": 151645,
+  "vision_start_token_id": 151652,
+  "vision_end_token_id": 151653,
+  "vision_token_id": 151654,
+  "image_token_id": 151655,
+  "video_token_id": 151656,
+  "hidden_act": "silu",
+  "hidden_size": 5120,
+  "initializer_range": 0.02,
+  "intermediate_size": 20480,
+  "max_position_embeddings": 128000,
+  "max_window_layers": 70,
+  "model_type": "sapnous_t1",
+  "num_attention_heads": 40,
+  "num_hidden_layers": 36,
+  "num_key_value_heads": 8,
+  "rms_norm_eps": 1e-06,
+  "rope_theta": 1000000.0,
+  "sliding_window": 32768,
+  "tie_word_embeddings": true,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.41.2",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "vision_config": {
+    "depth": 32,
+    "hidden_act": "silu",
+    "hidden_size": 1280,
+    "intermediate_size": 3420,
+    "num_heads": 16,
+    "in_chans": 3,
+    "out_hidden_size": 2048,
+    "patch_size": 14,
+    "spatial_merge_size": 2,
+    "spatial_patch_size": 14,
+    "window_size": 112,
+    "fullatt_block_indexes": [
+      7,
+      15,
+      23,
+      31
+    ],
+    "tokens_per_second": 2,
+    "temporal_patch_size": 2
+  },
+  "rope_scaling": {
+    "type": "mrope",
+    "mrope_section": [
+      16,
+      24,
+      24
+    ]
+  },
+  "vocab_size": 151936
+}

configuration_sapnous.py

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+from transformers.configuration_utils import PretrainedConfig
+from transformers.utils import logging
+from transformers import AutoConfig  # ✅ Correct Import
+
+logger = logging.get_logger(__name__)
+
+SAPNOUS_PRETRAINED_CONFIG_ARCHIVE_MAP = {
+    "Sapnous-AI/Sapnous-6B": "https://huggingface.co/Sapnous-AI/Sapnous-6B/resolve/main/config.json",
+}
+
+class SapnousT1Config(PretrainedConfig):
+    model_type = "sapnous_t1"
+
+    def __init__(
+        self,
+        vocab_size=151936,
+        hidden_size=5120,
+        intermediate_size=20480,
+        num_hidden_layers=36,
+        num_attention_heads=40,
+        num_key_value_heads=8,
+        hidden_act="silu",
+        max_position_embeddings=128000,
+        initializer_range=0.02,
+        rms_norm_eps=1e-6,
+        use_cache=True,
+        pad_token_id=None,
+        bos_token_id=151643,
+        eos_token_id=151645,
+        tie_word_embeddings=True,
+        vision_start_token_id=151652,
+        vision_end_token_id=151653,
+        vision_token_id=151654,
+        image_token_id=151655,
+        video_token_id=151656,
+        vision_config=None,
+        rope_theta=1000000.0,
+        sliding_window=32768,
+        use_sliding_window=False,
+        max_window_layers=70,
+        attention_dropout=0.0,
+        rope_scaling=None,
+        scoring_func="softmax",
+        aux_loss_alpha=0.001,
+        seq_aux=True,
+        **kwargs
+    ):
+        super().__init__(
+            pad_token_id=pad_token_id,
+            bos_token_id=bos_token_id,
+            eos_token_id=eos_token_id,
+            tie_word_embeddings=tie_word_embeddings,
+            **kwargs,
+        )
+
+        self.vocab_size = vocab_size
+        self.max_position_embeddings = max_position_embeddings
+        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_key_value_heads = num_key_value_heads
+        self.hidden_act = hidden_act
+        self.initializer_range = initializer_range
+        self.rms_norm_eps = rms_norm_eps
+        self.use_cache = use_cache
+        self.vision_start_token_id = vision_start_token_id
+        self.vision_end_token_id = vision_end_token_id
+        self.vision_token_id = vision_token_id
+        self.image_token_id = image_token_id
+        self.video_token_id = video_token_id
+        self.vision_config = vision_config
+        self.rope_theta = rope_theta
+        self.sliding_window = sliding_window
+        self.use_sliding_window = use_sliding_window
+        self.max_window_layers = max_window_layers
+        self.attention_dropout = attention_dropout
+        self.rope_scaling = rope_scaling
+        self.scoring_func = scoring_func
+        self.aux_loss_alpha = aux_loss_alpha
+        self.seq_aux = seq_aux
+
+    model_type = "sapnous_t1"
+    keys_to_ignore_at_inference = ["past_key_values"]
+
+# ✅ Register after defining the class
+AutoConfig.register("sapnous_t1", SapnousT1Config)

convert_to_gguf.py

@@ -0,0 +1,49 @@
+import os
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from ctransformers import AutoModelForCausalLM as GGUFModel
+
+def convert_to_gguf(model_path, output_path):
+    # Load the model and tokenizer with vision-language support
+    model = AutoModelForCausalLM.from_pretrained(
+        model_path,
+        trust_remote_code=True,
+        device_map='auto',
+        torch_dtype=torch.float16  # Use FP16 for memory efficiency
+    )
+    tokenizer = AutoTokenizer.from_pretrained(
+        model_path,
+        trust_remote_code=True
+    )
+    
+    # Save in GGUF format
+    model.save_pretrained(output_path, safe_serialization=True)
+    tokenizer.save_pretrained(output_path)
+    
+    # Convert to GGUF using ctransformers with SapnousT1 architecture settings
+    gguf_model = GGUFModel.from_pretrained(
+        output_path,
+        model_type='llama',  # Base architecture type
+        gpu_layers=0,  # CPU only for conversion
+        config={
+            'context_length': 32768,  # Match model's sliding window size
+            'attention_type': 'multiquery',  # For efficient attention
+            'num_attention_heads': 40,  # Match model's head count
+            'num_key_value_heads': 8,  # Match model's KV head count
+            'hidden_size': 5120,  # Match model's hidden size
+            'intermediate_size': 20480,  # Match model's intermediate size
+            'max_position_embeddings': 128000  # Match model's max positions
+        }
+    )
+    
+    print(f"Model converted and saved to {output_path}")
+    return gguf_model
+
+if __name__ == '__main__':
+    model_path = os.path.dirname(os.path.abspath(__file__))
+    output_path = os.path.join(model_path, 'gguf_model')
+    
+    if not os.path.exists(output_path):
+        os.makedirs(output_path)
+        
+    convert_to_gguf(model_path, output_path)

generation_config.json

@@ -0,0 +1,12 @@
+{
+  "bos_token_id": 151643,
+  "pad_token_id": 151643,
+  "do_sample": true,
+  "eos_token_id": [
+    151645,
+    151643
+  ],
+  "repetition_penalty": 1.05,
+  "temperature": 0.00001,
+  "transformers_version": "4.49.0"
+}

model-00001-of-00005.safetensors

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model.py

@@ -0,0 +1,26 @@
+from transformers import PreTrainedModel, AutoConfig
+import torch
+import torch.nn as nn
+
+class SapnousT1ForCausalLM(PreTrainedModel):
+    config_class = AutoConfig
+
+    def __init__(self, config):
+        super().__init__(config)
+        self.hidden_size = config.hidden_size
+        self.embed_tokens = nn.Embedding(config.vocab_size, config.hidden_size)
+        self.layers = nn.ModuleList([
+            nn.Linear(config.hidden_size, config.hidden_size) for _ in range(config.num_hidden_layers)
+        ])
+        self.lm_head = nn.Linear(config.hidden_size, config.vocab_size, bias=False)
+
+    def forward(self, input_ids):
+        hidden_states = self.embed_tokens(input_ids)
+        for layer in self.layers:
+            hidden_states = layer(hidden_states)
+        logits = self.lm_head(hidden_states)
+        return logits
+
+# Register model with transformers
+from transformers import AutoModelForCausalLM
+AutoModelForCausalLM.register(SapnousT1ForCausalLM, "sapnous_t1")

model.safetensors.index.json

@@ -0,0 +1,736 @@
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+    "visual.blocks.8.mlp.gate_proj.weight": "model-00001-of-00005.safetensors",
+    "visual.blocks.8.mlp.up_proj.bias": "model-00001-of-00005.safetensors",
+    "visual.blocks.8.mlp.up_proj.weight": "model-00001-of-00005.safetensors",
+    "visual.blocks.8.norm1.weight": "model-00001-of-00005.safetensors",
+    "visual.blocks.8.norm2.weight": "model-00001-of-00005.safetensors",
+    "visual.blocks.9.attn.proj.bias": "model-00001-of-00005.safetensors",
+    "visual.blocks.9.attn.proj.weight": "model-00001-of-00005.safetensors",
+    "visual.blocks.9.attn.qkv.bias": "model-00001-of-00005.safetensors",
+    "visual.blocks.9.attn.qkv.weight": "model-00001-of-00005.safetensors",
+    "visual.blocks.9.mlp.down_proj.bias": "model-00001-of-00005.safetensors",
+    "visual.blocks.9.mlp.down_proj.weight": "model-00001-of-00005.safetensors",
+    "visual.blocks.9.mlp.gate_proj.bias": "model-00001-of-00005.safetensors",
+    "visual.blocks.9.mlp.gate_proj.weight": "model-00001-of-00005.safetensors",
+    "visual.blocks.9.mlp.up_proj.bias": "model-00001-of-00005.safetensors",
+    "visual.blocks.9.mlp.up_proj.weight": "model-00001-of-00005.safetensors",
+    "visual.blocks.9.norm1.weight": "model-00001-of-00005.safetensors",
+    "visual.blocks.9.norm2.weight": "model-00001-of-00005.safetensors",
+    "visual.merger.ln_q.weight": "model-00001-of-00005.safetensors",
+    "visual.merger.mlp.0.bias": "model-00001-of-00005.safetensors",
+    "visual.merger.mlp.0.weight": "model-00001-of-00005.safetensors",
+    "visual.merger.mlp.2.bias": "model-00001-of-00005.safetensors",
+    "visual.merger.mlp.2.weight": "model-00001-of-00005.safetensors",
+    "visual.patch_embed.proj.weight": "model-00001-of-00005.safetensors"
+  }
+}

modeling_sapnous.py

@@ -0,0 +1,53 @@
+import torch
+import torch.nn as nn
+from transformers import PreTrainedModel, AutoModelForCausalLM
+from configuration_sapnous import SapnousT1Config  # Ensure this file is correct
+
+class SapnousT1PreTrainedModel(PreTrainedModel):
+    """Base class for all Sapnous-T1 models."""
+    config_class = SapnousT1Config
+
+    def __init__(self, config: SapnousT1Config):
+        super().__init__(config)
+        self.config = config
+
+    def _init_weights(self, module):
+        """Initialize weights if required."""
+        if isinstance(module, nn.Linear):
+            module.weight.data.normal_(mean=0.0, std=self.config.initializer_range)
+            if module.bias is not None:
+                module.bias.data.zero_()
+
+class SapnousT1Model(SapnousT1PreTrainedModel):
+    """Base Transformer Model"""
+    def __init__(self, config: SapnousT1Config):
+        super().__init__(config)
+        self.embeddings = nn.Embedding(config.vocab_size, config.hidden_size)
+        self.encoder = nn.TransformerEncoder(
+            nn.TransformerEncoderLayer(
+                d_model=config.hidden_size,
+                nhead=config.num_attention_heads
+            ),
+            num_layers=config.num_hidden_layers
+        )
+        self.lm_head = nn.Linear(config.hidden_size, config.vocab_size)
+
+    def forward(self, input_ids):
+        x = self.embeddings(input_ids)
+        x = self.encoder(x)
+        return self.lm_head(x)
+
+class SapnousT1ForCausalLM(SapnousT1PreTrainedModel):
+    """Sapnous-T1 Model for Causal LM (Text Generation)"""
+    def __init__(self, config: SapnousT1Config):
+        super().__init__(config)
+        self.model = SapnousT1Model(config)
+        self.lm_head = nn.Linear(config.hidden_size, config.vocab_size, bias=False)
+
+    def forward(self, input_ids):
+        hidden_states = self.model(input_ids)
+        logits = self.lm_head(hidden_states)
+        return logits
+
+# ✅ Register the model properly
+AutoModelForCausalLM.register(SapnousT1Config, SapnousT1ForCausalLM)

preprocessor_config.json

@@ -0,0 +1,19 @@
+{
+  "min_pixels": 3136,
+  "max_pixels": 12845056,
+  "patch_size": 14,
+  "temporal_patch_size": 2,
+  "merge_size": 2,
+  "image_mean": [
+    0.48145466,
+    0.4578275,
+    0.40821073
+  ],
+  "image_std": [
+    0.26862954,
+    0.26130258,
+    0.27577711
+  ],
+  "image_processor_type": "Sapnous12BImageProcessor",
+  "processor_class": "Sapnous12BProcessor"
+}

setup.py

@@ -0,0 +1,15 @@
+import sys
+import os
+
+# Add the current directory to sys.path so Python can find `configuration_sapnous.py`
+sys.path.append(os.path.dirname(os.path.abspath(__file__)))
+
+from transformers import AutoModel, AutoConfig
+from configuration_sapnous import SapnousT1Config  # Now it should work
+
+model_path = r"E:\git\Sapnous-47B\Sapnous-6B"
+
+config = AutoConfig.from_pretrained(model_path, trust_remote_code=True)
+model = AutoModel.from_pretrained(model_path, config=config, trust_remote_code=True)
+
+print("Model loaded successfully!")

tokenizer_config.json

@@ -0,0 +1,207 @@
+{
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "151643": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151644": {
+      "content": "<|im_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151645": {
+      "content": "<|im_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151646": {
+      "content": "<|object_ref_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151647": {
+      "content": "<|object_ref_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151648": {
+      "content": "<|box_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151649": {
+      "content": "<|box_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151650": {
+      "content": "<|quad_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151651": {
+      "content": "<|quad_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151652": {
+      "content": "<|vision_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151653": {
+      "content": "<|vision_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151654": {
+      "content": "<|vision_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151655": {
+      "content": "<|image_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151656": {
+      "content": "<|video_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151657": {
+      "content": "<tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151658": {
+      "content": "</tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151659": {
+      "content": "<|fim_prefix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151660": {
+      "content": "<|fim_middle|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151661": {
+      "content": "<|fim_suffix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151662": {
+      "content": "<|fim_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151663": {
+      "content": "<|repo_name|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151664": {
+      "content": "<|file_sep|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    }
+  },
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
+  "bos_token": null,
+  "chat_template": "{%- if tools %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if messages[0]['role'] == 'system' %}\n        {{- messages[0]['content'] }}\n    {%- else %}\n        {{- 'You are a helpful assistant.' }}\n    {%- endif %}\n    {{- \"\\n\\n# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n    {%- for tool in tools %}\n        {{- \"\\n\" }}\n        {{- tool | tojson }}\n    {%- endfor %}\n    {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n    {%- if messages[0]['role'] == 'system' %}\n        {{- '<|im_start|>system\\n' + messages[0]['content'] + '<|im_end|>\\n' }}\n    {%- else %}\n        {{- '<|im_start|>system\\nYou are a helpful assistant.<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n    {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n        {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {{- '<|im_start|>' + message.role }}\n        {%- if message.content %}\n            {{- '\\n' + message.content }}\n        {%- endif %}\n        {%- for tool_call in message.tool_calls %}\n            {%- if tool_call.function is defined %}\n                {%- set tool_call = tool_call.function %}\n            {%- endif %}\n            {{- '\\n<tool_call>\\n{\"name\": \"' }}\n            {{- tool_call.name }}\n            {{- '\", \"arguments\": ' }}\n            {{- tool_call.arguments | tojson }}\n            {{- '}\\n</tool_call>' }}\n        {%- endfor %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {{- message.content }}\n        {{- '\\n</tool_response>' }}\n        {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n            {{- '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "model_max_length": 131072,
+  "pad_token": "<|endoftext|>",
+  "split_special_tokens": false,
+  "tokenizer_class": "SapnousT1Tokenizer",
+  "unk_token": null,
+  "add_bos_token": false
+}