Upload folder using huggingface_hub
Browse files- .gitattributes +1 -34
- LICENSE +211 -0
- README.md +14 -3
- Verus-4b-r2/chat_template.jinja +154 -0
- Verus-4b-r2/config.json +81 -0
- Verus-4b-r2/model-00001-of-00002.safetensors +3 -0
- Verus-4b-r2/model-00002-of-00002.safetensors +3 -0
- Verus-4b-r2/model.safetensors.index.json +443 -0
- Verus-4b-r2/tokenizer.json +3 -0
- Verus-4b-r2/tokenizer_config.json +38 -0
- chat_template.jinja +1 -0
- config.json +10 -0
- merges.txt +168 -0
- model.safetensors.index.json +7 -0
- preprocessor_config.json +32 -0
- tokenizer.json +992 -0
- tokenizer_config.json +94 -0
- train.py +450 -0
- upload_to_hf.py +30 -0
- video_preprocessor_config.json +6 -0
- vocab.json +858 -0
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| 195 |
+
limitations under the License.
|
| 196 |
+
|
| 197 |
+
---
|
| 198 |
+
|
| 199 |
+
THIRD-PARTY NOTICES
|
| 200 |
+
|
| 201 |
+
This model is derived from Qwen/Qwen3.5-0.8B, which is also licensed
|
| 202 |
+
under the Apache License, Version 2.0.
|
| 203 |
+
|
| 204 |
+
Copyright 2025 Alibaba Cloud
|
| 205 |
+
|
| 206 |
+
The vision encoder components follow the CLIP architecture introduced by
|
| 207 |
+
OpenAI and are used under its respective open-source license terms.
|
| 208 |
+
|
| 209 |
+
The LLaVA-Next multimodal integration architecture is based on research
|
| 210 |
+
originally published by Haotian Liu et al. and adapted under the
|
| 211 |
+
Apache 2.0 License.
|
README.md
CHANGED
|
@@ -1,3 +1,14 @@
|
|
| 1 |
-
-
|
| 2 |
-
|
| 3 |
-
--
|
|
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|
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|
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|
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|
|
|
|
|
|
|
| 1 |
+
# Verus-4B
|
| 2 |
+
|
| 3 |
+
This folder is a scaffold for a `Verus-4B` Hugging Face-style repository based on the file layout shown in the screenshot.
|
| 4 |
+
|
| 5 |
+
Included here:
|
| 6 |
+
- shared tokenizer and processor assets copied from the local `Verus-0.8b` folder
|
| 7 |
+
- a `chat_template.jinja` companion file
|
| 8 |
+
- placeholder metadata files for the missing `4B` weights/config
|
| 9 |
+
|
| 10 |
+
Not included yet:
|
| 11 |
+
- `model.safetensors-00001-of-00002.safetensors`
|
| 12 |
+
- `model.safetensors-00002-of-00002.safetensors`
|
| 13 |
+
|
| 14 |
+
Before using this as a real model repo, replace the placeholder `config.json`, `model.safetensors.index.json`, and `video_preprocessor_config.json` with the actual Verus-4B files.
|
Verus-4b-r2/chat_template.jinja
ADDED
|
@@ -0,0 +1,154 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
|
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|
|
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|
|
|
|
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|
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|
|
|
|
|
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|
|
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|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{%- set image_count = namespace(value=0) %}
|
| 2 |
+
{%- set video_count = namespace(value=0) %}
|
| 3 |
+
{%- macro render_content(content, do_vision_count, is_system_content=false) %}
|
| 4 |
+
{%- if content is string %}
|
| 5 |
+
{{- content }}
|
| 6 |
+
{%- elif content is iterable and content is not mapping %}
|
| 7 |
+
{%- for item in content %}
|
| 8 |
+
{%- if 'image' in item or 'image_url' in item or item.type == 'image' %}
|
| 9 |
+
{%- if is_system_content %}
|
| 10 |
+
{{- raise_exception('System message cannot contain images.') }}
|
| 11 |
+
{%- endif %}
|
| 12 |
+
{%- if do_vision_count %}
|
| 13 |
+
{%- set image_count.value = image_count.value + 1 %}
|
| 14 |
+
{%- endif %}
|
| 15 |
+
{%- if add_vision_id %}
|
| 16 |
+
{{- 'Picture ' ~ image_count.value ~ ': ' }}
|
| 17 |
+
{%- endif %}
|
| 18 |
+
{{- '<|vision_start|><|image_pad|><|vision_end|>' }}
|
| 19 |
+
{%- elif 'video' in item or item.type == 'video' %}
|
| 20 |
+
{%- if is_system_content %}
|
| 21 |
+
{{- raise_exception('System message cannot contain videos.') }}
|
| 22 |
+
{%- endif %}
|
| 23 |
+
{%- if do_vision_count %}
|
| 24 |
+
{%- set video_count.value = video_count.value + 1 %}
|
| 25 |
+
{%- endif %}
|
| 26 |
+
{%- if add_vision_id %}
|
| 27 |
+
{{- 'Video ' ~ video_count.value ~ ': ' }}
|
| 28 |
+
{%- endif %}
|
| 29 |
+
{{- '<|vision_start|><|video_pad|><|vision_end|>' }}
|
| 30 |
+
{%- elif 'text' in item %}
|
| 31 |
+
{{- item.text }}
|
| 32 |
+
{%- else %}
|
| 33 |
+
{{- raise_exception('Unexpected item type in content.') }}
|
| 34 |
+
{%- endif %}
|
| 35 |
+
{%- endfor %}
|
| 36 |
+
{%- elif content is none or content is undefined %}
|
| 37 |
+
{{- '' }}
|
| 38 |
+
{%- else %}
|
| 39 |
+
{{- raise_exception('Unexpected content type.') }}
|
| 40 |
+
{%- endif %}
|
| 41 |
+
{%- endmacro %}
|
| 42 |
+
{%- if not messages %}
|
| 43 |
+
{{- raise_exception('No messages provided.') }}
|
| 44 |
+
{%- endif %}
|
| 45 |
+
{%- if tools and tools is iterable and tools is not mapping %}
|
| 46 |
+
{{- '<|im_start|>system\n' }}
|
| 47 |
+
{{- "# Tools\n\nYou have access to the following functions:\n\n<tools>" }}
|
| 48 |
+
{%- for tool in tools %}
|
| 49 |
+
{{- "\n" }}
|
| 50 |
+
{{- tool | tojson }}
|
| 51 |
+
{%- endfor %}
|
| 52 |
+
{{- "\n</tools>" }}
|
| 53 |
+
{{- '\n\nIf you choose to call a function ONLY reply in the following format with NO suffix:\n\n<tool_call>\n<function=example_function_name>\n<parameter=example_parameter_1>\nvalue_1\n</parameter>\n<parameter=example_parameter_2>\nThis is the value for the second parameter\nthat can span\nmultiple lines\n</parameter>\n</function>\n</tool_call>\n\n<IMPORTANT>\nReminder:\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\n- Required parameters MUST be specified\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\n</IMPORTANT>' }}
|
| 54 |
+
{%- if messages[0].role == 'system' %}
|
| 55 |
+
{%- set content = render_content(messages[0].content, false, true)|trim %}
|
| 56 |
+
{%- if content %}
|
| 57 |
+
{{- '\n\n' + content }}
|
| 58 |
+
{%- endif %}
|
| 59 |
+
{%- endif %}
|
| 60 |
+
{{- '<|im_end|>\n' }}
|
| 61 |
+
{%- else %}
|
| 62 |
+
{%- if messages[0].role == 'system' %}
|
| 63 |
+
{%- set content = render_content(messages[0].content, false, true)|trim %}
|
| 64 |
+
{{- '<|im_start|>system\n' + content + '<|im_end|>\n' }}
|
| 65 |
+
{%- endif %}
|
| 66 |
+
{%- endif %}
|
| 67 |
+
{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
|
| 68 |
+
{%- for message in messages[::-1] %}
|
| 69 |
+
{%- set index = (messages|length - 1) - loop.index0 %}
|
| 70 |
+
{%- if ns.multi_step_tool and message.role == "user" %}
|
| 71 |
+
{%- set content = render_content(message.content, false)|trim %}
|
| 72 |
+
{%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}
|
| 73 |
+
{%- set ns.multi_step_tool = false %}
|
| 74 |
+
{%- set ns.last_query_index = index %}
|
| 75 |
+
{%- endif %}
|
| 76 |
+
{%- endif %}
|
| 77 |
+
{%- endfor %}
|
| 78 |
+
{%- if ns.multi_step_tool %}
|
| 79 |
+
{{- raise_exception('No user query found in messages.') }}
|
| 80 |
+
{%- endif %}
|
| 81 |
+
{%- for message in messages %}
|
| 82 |
+
{%- set content = render_content(message.content, true)|trim %}
|
| 83 |
+
{%- if message.role == "system" %}
|
| 84 |
+
{%- if not loop.first %}
|
| 85 |
+
{{- raise_exception('System message must be at the beginning.') }}
|
| 86 |
+
{%- endif %}
|
| 87 |
+
{%- elif message.role == "user" %}
|
| 88 |
+
{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
|
| 89 |
+
{%- elif message.role == "assistant" %}
|
| 90 |
+
{%- set reasoning_content = '' %}
|
| 91 |
+
{%- if message.reasoning_content is string %}
|
| 92 |
+
{%- set reasoning_content = message.reasoning_content %}
|
| 93 |
+
{%- else %}
|
| 94 |
+
{%- if '</think>' in content %}
|
| 95 |
+
{%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
|
| 96 |
+
{%- set content = content.split('</think>')[-1].lstrip('\n') %}
|
| 97 |
+
{%- endif %}
|
| 98 |
+
{%- endif %}
|
| 99 |
+
{%- set reasoning_content = reasoning_content|trim %}
|
| 100 |
+
{%- if loop.index0 > ns.last_query_index %}
|
| 101 |
+
{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content + '\n</think>\n\n' + content }}
|
| 102 |
+
{%- else %}
|
| 103 |
+
{{- '<|im_start|>' + message.role + '\n' + content }}
|
| 104 |
+
{%- endif %}
|
| 105 |
+
{%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}
|
| 106 |
+
{%- for tool_call in message.tool_calls %}
|
| 107 |
+
{%- if tool_call.function is defined %}
|
| 108 |
+
{%- set tool_call = tool_call.function %}
|
| 109 |
+
{%- endif %}
|
| 110 |
+
{%- if loop.first %}
|
| 111 |
+
{%- if content|trim %}
|
| 112 |
+
{{- '\n\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 113 |
+
{%- else %}
|
| 114 |
+
{{- '<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 115 |
+
{%- endif %}
|
| 116 |
+
{%- else %}
|
| 117 |
+
{{- '\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 118 |
+
{%- endif %}
|
| 119 |
+
{%- if tool_call.arguments is defined %}
|
| 120 |
+
{%- for args_name, args_value in tool_call.arguments|items %}
|
| 121 |
+
{{- '<parameter=' + args_name + '>\n' }}
|
| 122 |
+
{%- set args_value = args_value | tojson | safe if args_value is mapping or (args_value is sequence and args_value is not string) else args_value | string %}
|
| 123 |
+
{{- args_value }}
|
| 124 |
+
{{- '\n</parameter>\n' }}
|
| 125 |
+
{%- endfor %}
|
| 126 |
+
{%- endif %}
|
| 127 |
+
{{- '</function>\n</tool_call>' }}
|
| 128 |
+
{%- endfor %}
|
| 129 |
+
{%- endif %}
|
| 130 |
+
{{- '<|im_end|>\n' }}
|
| 131 |
+
{%- elif message.role == "tool" %}
|
| 132 |
+
{%- if loop.previtem and loop.previtem.role != "tool" %}
|
| 133 |
+
{{- '<|im_start|>user' }}
|
| 134 |
+
{%- endif %}
|
| 135 |
+
{{- '\n<tool_response>\n' }}
|
| 136 |
+
{{- content }}
|
| 137 |
+
{{- '\n</tool_response>' }}
|
| 138 |
+
{%- if not loop.last and loop.nextitem.role != "tool" %}
|
| 139 |
+
{{- '<|im_end|>\n' }}
|
| 140 |
+
{%- elif loop.last %}
|
| 141 |
+
{{- '<|im_end|>\n' }}
|
| 142 |
+
{%- endif %}
|
| 143 |
+
{%- else %}
|
| 144 |
+
{{- raise_exception('Unexpected message role.') }}
|
| 145 |
+
{%- endif %}
|
| 146 |
+
{%- endfor %}
|
| 147 |
+
{%- if add_generation_prompt %}
|
| 148 |
+
{{- '<|im_start|>assistant\n' }}
|
| 149 |
+
{%- if enable_thinking is defined and enable_thinking is false %}
|
| 150 |
+
{{- '<think>\n\n</think>\n\n' }}
|
| 151 |
+
{%- else %}
|
| 152 |
+
{{- '<think>\n' }}
|
| 153 |
+
{%- endif %}
|
| 154 |
+
{%- endif %}
|
Verus-4b-r2/config.json
ADDED
|
@@ -0,0 +1,81 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"attention_bias": false,
|
| 3 |
+
"attention_dropout": 0.0,
|
| 4 |
+
"attn_output_gate": true,
|
| 5 |
+
"bos_token_id": null,
|
| 6 |
+
"dtype": "bfloat16",
|
| 7 |
+
"eos_token_id": 248044,
|
| 8 |
+
"full_attention_interval": 4,
|
| 9 |
+
"head_dim": 256,
|
| 10 |
+
"hidden_act": "silu",
|
| 11 |
+
"hidden_size": 2560,
|
| 12 |
+
"initializer_range": 0.02,
|
| 13 |
+
"intermediate_size": 9216,
|
| 14 |
+
"layer_types": [
|
| 15 |
+
"linear_attention",
|
| 16 |
+
"linear_attention",
|
| 17 |
+
"linear_attention",
|
| 18 |
+
"full_attention",
|
| 19 |
+
"linear_attention",
|
| 20 |
+
"linear_attention",
|
| 21 |
+
"linear_attention",
|
| 22 |
+
"full_attention",
|
| 23 |
+
"linear_attention",
|
| 24 |
+
"linear_attention",
|
| 25 |
+
"linear_attention",
|
| 26 |
+
"full_attention",
|
| 27 |
+
"linear_attention",
|
| 28 |
+
"linear_attention",
|
| 29 |
+
"linear_attention",
|
| 30 |
+
"full_attention",
|
| 31 |
+
"linear_attention",
|
| 32 |
+
"linear_attention",
|
| 33 |
+
"linear_attention",
|
| 34 |
+
"full_attention",
|
| 35 |
+
"linear_attention",
|
| 36 |
+
"linear_attention",
|
| 37 |
+
"linear_attention",
|
| 38 |
+
"full_attention",
|
| 39 |
+
"linear_attention",
|
| 40 |
+
"linear_attention",
|
| 41 |
+
"linear_attention",
|
| 42 |
+
"full_attention",
|
| 43 |
+
"linear_attention",
|
| 44 |
+
"linear_attention",
|
| 45 |
+
"linear_attention",
|
| 46 |
+
"full_attention"
|
| 47 |
+
],
|
| 48 |
+
"linear_conv_kernel_dim": 4,
|
| 49 |
+
"linear_key_head_dim": 128,
|
| 50 |
+
"linear_num_key_heads": 16,
|
| 51 |
+
"linear_num_value_heads": 32,
|
| 52 |
+
"linear_value_head_dim": 128,
|
| 53 |
+
"mamba_ssm_dtype": "float32",
|
| 54 |
+
"max_position_embeddings": 262144,
|
| 55 |
+
"mlp_only_layers": [],
|
| 56 |
+
"model_type": "qwen3_5_text",
|
| 57 |
+
"mtp_num_hidden_layers": 1,
|
| 58 |
+
"mtp_use_dedicated_embeddings": false,
|
| 59 |
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"model.layers.31.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
| 435 |
+
"model.layers.31.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
| 436 |
+
"model.layers.31.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
| 437 |
+
"model.layers.31.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
| 438 |
+
"model.layers.31.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
| 439 |
+
"model.norm.weight": "model-00002-of-00002.safetensors",
|
| 440 |
+
"model.rotary_emb.inv_freq": "model-00002-of-00002.safetensors",
|
| 441 |
+
"model.rotary_emb.original_inv_freq": "model-00002-of-00002.safetensors"
|
| 442 |
+
}
|
| 443 |
+
}
|
Verus-4b-r2/tokenizer.json
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:2dc51b3d1df32a61c278f91ef1f2adcdec3b75aff536bb29d9886249e354a311
|
| 3 |
+
size 19989621
|
Verus-4b-r2/tokenizer_config.json
ADDED
|
@@ -0,0 +1,38 @@
|
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|
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|
| 1 |
+
{
|
| 2 |
+
"add_prefix_space": false,
|
| 3 |
+
"audio_bos_token": "<|audio_start|>",
|
| 4 |
+
"audio_eos_token": "<|audio_end|>",
|
| 5 |
+
"audio_token": "<|audio_pad|>",
|
| 6 |
+
"backend": "tokenizers",
|
| 7 |
+
"bos_token": null,
|
| 8 |
+
"clean_up_tokenization_spaces": false,
|
| 9 |
+
"eos_token": "<|endoftext|>",
|
| 10 |
+
"errors": "replace",
|
| 11 |
+
"image_token": "<|image_pad|>",
|
| 12 |
+
"is_local": true,
|
| 13 |
+
"max_length": 512,
|
| 14 |
+
"model_max_length": 262144,
|
| 15 |
+
"model_specific_special_tokens": {
|
| 16 |
+
"audio_bos_token": "<|audio_start|>",
|
| 17 |
+
"audio_eos_token": "<|audio_end|>",
|
| 18 |
+
"audio_token": "<|audio_pad|>",
|
| 19 |
+
"image_token": "<|image_pad|>",
|
| 20 |
+
"video_token": "<|video_pad|>",
|
| 21 |
+
"vision_bos_token": "<|vision_start|>",
|
| 22 |
+
"vision_eos_token": "<|vision_end|>"
|
| 23 |
+
},
|
| 24 |
+
"pad_to_multiple_of": null,
|
| 25 |
+
"pad_token": "<|endoftext|>",
|
| 26 |
+
"pad_token_type_id": 0,
|
| 27 |
+
"padding_side": "right",
|
| 28 |
+
"pretokenize_regex": "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?[\\p{L}\\p{M}]+|\\p{N}| ?[^\\s\\p{L}\\p{M}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
|
| 29 |
+
"split_special_tokens": false,
|
| 30 |
+
"stride": 0,
|
| 31 |
+
"tokenizer_class": "TokenizersBackend",
|
| 32 |
+
"truncation_side": "right",
|
| 33 |
+
"truncation_strategy": "longest_first",
|
| 34 |
+
"unk_token": null,
|
| 35 |
+
"video_token": "<|video_pad|>",
|
| 36 |
+
"vision_bos_token": "<|vision_start|>",
|
| 37 |
+
"vision_eos_token": "<|vision_end|>"
|
| 38 |
+
}
|
chat_template.jinja
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
{%- if messages[0]['role'] == 'system' %}{%- set system_message = messages[0]['content'] %}{%- set loop_messages = messages[1:] %}{%- else %}{%- set system_message = 'You are Verus, a helpful multimodal coding assistant. You specialize in converting UI mockups, wireframes, and architecture diagrams into production-ready code.' %}{%- set loop_messages = messages %}{%- endif %}{{- '<|im_start|>system\n' + system_message + '<|im_end|>\n' }}{%- for message in loop_messages %}{%- if message['role'] == 'user' %}{{- '<|im_start|>user\n' }}{%- if message['content'] is iterable and message['content'] is not string %}{%- for item in message['content'] %}{%- if item['type'] == 'image' %}{{- '<|vision_start|><|image_pad|><|vision_end|>' }}{%- elif item['type'] == 'text' %}{{- item['text'] }}{%- endif %}{%- endfor %}{%- else %}{{- message['content'] }}{%- endif %}{{- '<|im_end|>\n' }}{%- elif message['role'] == 'assistant' %}{{- '<|im_start|>assistant\n' }}{%- if message['content'] is not none %}{{- message['content'] }}{%- endif %}{%- if not loop.last or not add_generation_prompt %}{{- '<|im_end|>\n' }}{%- endif %}{%- endif %}{%- endfor %}{%- if add_generation_prompt %}{{- '<|im_start|>assistant\n' }}{%- endif %}
|
config.json
ADDED
|
@@ -0,0 +1,10 @@
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|
| 1 |
+
{
|
| 2 |
+
"_name_or_path": "8F-ai/Verus-4B",
|
| 3 |
+
"model_type": "llava_next",
|
| 4 |
+
"torch_dtype": "bfloat16",
|
| 5 |
+
"transformers_version": "4.52.0",
|
| 6 |
+
"architectures": [
|
| 7 |
+
"LlavaNextForConditionalGeneration"
|
| 8 |
+
],
|
| 9 |
+
"note": "Placeholder scaffold created from the local Verus-0.8b repository. Replace this file with the actual Verus-4B config before loading the model."
|
| 10 |
+
}
|
merges.txt
ADDED
|
@@ -0,0 +1,168 @@
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|
| 1 |
+
e r
|
| 2 |
+
i n
|
| 3 |
+
r e
|
| 4 |
+
o n
|
| 5 |
+
a n
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| 6 |
+
s e
|
| 7 |
+
a t
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| 8 |
+
e n
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+
a r
|
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+
t i
|
| 11 |
+
a l
|
| 12 |
+
t e
|
| 13 |
+
i c
|
| 14 |
+
i s
|
| 15 |
+
i t
|
| 16 |
+
s t
|
| 17 |
+
e s
|
| 18 |
+
e d
|
| 19 |
+
f i
|
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+
f o
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+
c o
|
| 22 |
+
c l
|
| 23 |
+
t r
|
| 24 |
+
l i
|
| 25 |
+
l o
|
| 26 |
+
t h
|
| 27 |
+
n d
|
| 28 |
+
n t
|
| 29 |
+
r i
|
| 30 |
+
r o
|
| 31 |
+
l a
|
| 32 |
+
m e
|
| 33 |
+
p a
|
| 34 |
+
n c
|
| 35 |
+
p e
|
| 36 |
+
e x
|
| 37 |
+
u n
|
| 38 |
+
n g
|
| 39 |
+
p o
|
| 40 |
+
a c
|
| 41 |
+
m o
|
| 42 |
+
s i
|
| 43 |
+
Ġ Ġ
|
| 44 |
+
Ġ t
|
| 45 |
+
Ġ a
|
| 46 |
+
Ġ i
|
| 47 |
+
Ġ s
|
| 48 |
+
Ġ r
|
| 49 |
+
Ġ f
|
| 50 |
+
Ġ c
|
| 51 |
+
Ġ d
|
| 52 |
+
Ġ p
|
| 53 |
+
Ġ m
|
| 54 |
+
Ġ w
|
| 55 |
+
Ġ n
|
| 56 |
+
Ġ b
|
| 57 |
+
Ġ e
|
| 58 |
+
Ġ l
|
| 59 |
+
Ġ g
|
| 60 |
+
Ġ h
|
| 61 |
+
Ġ o
|
| 62 |
+
Ġ v
|
| 63 |
+
Ġ u
|
| 64 |
+
Ġ y
|
| 65 |
+
e r r
|
| 66 |
+
i ng
|
| 67 |
+
t ion
|
| 68 |
+
m ent
|
| 69 |
+
b le
|
| 70 |
+
d e
|
| 71 |
+
de f
|
| 72 |
+
Ġd ef
|
| 73 |
+
Ġde f
|
| 74 |
+
c la
|
| 75 |
+
cla s
|
| 76 |
+
clas s
|
| 77 |
+
Ġc lass
|
| 78 |
+
i m
|
| 79 |
+
im p
|
| 80 |
+
imp o
|
| 81 |
+
impo r
|
| 82 |
+
impor t
|
| 83 |
+
Ġi mport
|
| 84 |
+
r et
|
| 85 |
+
ret u
|
| 86 |
+
retu r
|
| 87 |
+
retur n
|
| 88 |
+
Ġr eturn
|
| 89 |
+
s el
|
| 90 |
+
sel f
|
| 91 |
+
Ġs elf
|
| 92 |
+
a s
|
| 93 |
+
as y
|
| 94 |
+
asy nc
|
| 95 |
+
Ġa sync
|
| 96 |
+
a w
|
| 97 |
+
aw a
|
| 98 |
+
awa i
|
| 99 |
+
awai t
|
| 100 |
+
Ġa wait
|
| 101 |
+
f un
|
| 102 |
+
fun c
|
| 103 |
+
func t
|
| 104 |
+
funct i
|
| 105 |
+
functi on
|
| 106 |
+
Ġf unction
|
| 107 |
+
c on
|
| 108 |
+
con s
|
| 109 |
+
cons t
|
| 110 |
+
Ġc onst
|
| 111 |
+
l et
|
| 112 |
+
Ġl et
|
| 113 |
+
e x
|
| 114 |
+
ex p
|
| 115 |
+
exp o
|
| 116 |
+
expo r
|
| 117 |
+
expor t
|
| 118 |
+
Ġe xport
|
| 119 |
+
= =
|
| 120 |
+
! =
|
| 121 |
+
< =
|
| 122 |
+
> =
|
| 123 |
+
= >
|
| 124 |
+
- >
|
| 125 |
+
: :
|
| 126 |
+
* *
|
| 127 |
+
/ /
|
| 128 |
+
& &
|
| 129 |
+
| |
|
| 130 |
+
? ?
|
| 131 |
+
. .
|
| 132 |
+
. ..
|
| 133 |
+
T r
|
| 134 |
+
Tr u
|
| 135 |
+
Tru e
|
| 136 |
+
ĠT rue
|
| 137 |
+
F al
|
| 138 |
+
Fal s
|
| 139 |
+
Fals e
|
| 140 |
+
ĠF alse
|
| 141 |
+
N on
|
| 142 |
+
Non e
|
| 143 |
+
ĠN one
|
| 144 |
+
n ul
|
| 145 |
+
nul l
|
| 146 |
+
Ġn ull
|
| 147 |
+
ĠĠ ĠĠ
|
| 148 |
+
Ċ Ġ
|
| 149 |
+
ĊĠ Ġ
|
| 150 |
+
ĊĠĠ ĠĠ
|
| 151 |
+
f n
|
| 152 |
+
Ġf n
|
| 153 |
+
p ub
|
| 154 |
+
Ġp ub
|
| 155 |
+
i mp
|
| 156 |
+
imp l
|
| 157 |
+
Ġi mpl
|
| 158 |
+
s tr
|
| 159 |
+
str u
|
| 160 |
+
stru c
|
| 161 |
+
struc t
|
| 162 |
+
Ġs truct
|
| 163 |
+
m at
|
| 164 |
+
mat ch
|
| 165 |
+
Ġm atch
|
| 166 |
+
t rait
|
| 167 |
+
Ġt rait
|
| 168 |
+
ĠĠĠĠ ĠĠĠĠ
|
model.safetensors.index.json
ADDED
|
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"metadata": {
|
| 3 |
+
"total_size": 0,
|
| 4 |
+
"note": "Placeholder index. Add the Verus-4B .safetensors shards later."
|
| 5 |
+
},
|
| 6 |
+
"weight_map": {}
|
| 7 |
+
}
|
preprocessor_config.json
ADDED
|
@@ -0,0 +1,32 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
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|
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|
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|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"auto_map": {
|
| 3 |
+
"AutoImageProcessor": "Qwen2VLImageProcessor",
|
| 4 |
+
"AutoProcessor": "Qwen2_5_VLProcessor"
|
| 5 |
+
},
|
| 6 |
+
"do_normalize": true,
|
| 7 |
+
"do_rescale": true,
|
| 8 |
+
"do_resize": true,
|
| 9 |
+
"image_mean": [
|
| 10 |
+
0.48145466,
|
| 11 |
+
0.4578275,
|
| 12 |
+
0.40821073
|
| 13 |
+
],
|
| 14 |
+
"image_std": [
|
| 15 |
+
0.26862954,
|
| 16 |
+
0.26130258,
|
| 17 |
+
0.27577711
|
| 18 |
+
],
|
| 19 |
+
"image_processor_type": "Qwen2VLImageProcessor",
|
| 20 |
+
"max_pixels": 1003520,
|
| 21 |
+
"merge_size": 2,
|
| 22 |
+
"min_pixels": 3136,
|
| 23 |
+
"patch_size": 14,
|
| 24 |
+
"processor_class": "Qwen2_5_VLProcessor",
|
| 25 |
+
"resample": 3,
|
| 26 |
+
"rescale_factor": 0.00392156862745098,
|
| 27 |
+
"size": {
|
| 28 |
+
"max_pixels": 1003520,
|
| 29 |
+
"min_pixels": 3136
|
| 30 |
+
},
|
| 31 |
+
"temporal_patch_size": 2
|
| 32 |
+
}
|
tokenizer.json
ADDED
|
@@ -0,0 +1,992 @@
|
|
|
|
|
|
|
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| 70 |
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| 96 |
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| 150 |
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| 151 |
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|
| 782 |
+
"Math.ceil": 845,
|
| 783 |
+
"Math.round": 846,
|
| 784 |
+
|
| 785 |
+
"tailwind": 850,
|
| 786 |
+
"webpack": 851,
|
| 787 |
+
"vite": 852,
|
| 788 |
+
"eslint": 853,
|
| 789 |
+
"prettier": 854,
|
| 790 |
+
"typescript": 855,
|
| 791 |
+
"docker": 856,
|
| 792 |
+
"kubernetes": 857,
|
| 793 |
+
"terraform": 858,
|
| 794 |
+
"github": 859,
|
| 795 |
+
"pipeline": 860,
|
| 796 |
+
"workflow": 861,
|
| 797 |
+
"json": 862,
|
| 798 |
+
"yaml": 863,
|
| 799 |
+
"toml": 864,
|
| 800 |
+
"protobuf": 865,
|
| 801 |
+
"graphql": 866,
|
| 802 |
+
"redis": 867,
|
| 803 |
+
"postgres": 868,
|
| 804 |
+
"mongodb": 869,
|
| 805 |
+
"sqlite": 870,
|
| 806 |
+
"kafka": 871,
|
| 807 |
+
|
| 808 |
+
"<|image|>": 32000,
|
| 809 |
+
"<|im_start|>": 32001,
|
| 810 |
+
"<|im_end|>": 32002,
|
| 811 |
+
"<|vision_start|>": 32003,
|
| 812 |
+
"<|vision_end|>": 32004,
|
| 813 |
+
"<|image_pad|>": 32005,
|
| 814 |
+
"<|fim_prefix|>": 32006,
|
| 815 |
+
"<|fim_middle|>": 32007,
|
| 816 |
+
"<|fim_suffix|>": 32008,
|
| 817 |
+
"<|fim_pad|>": 32009,
|
| 818 |
+
"<|endoftext|>": 32010
|
| 819 |
+
},
|
| 820 |
+
|
| 821 |
+
"merges": [
|
| 822 |
+
"e r",
|
| 823 |
+
"i n",
|
| 824 |
+
"r e",
|
| 825 |
+
"o n",
|
| 826 |
+
"a n",
|
| 827 |
+
"s e",
|
| 828 |
+
"a t",
|
| 829 |
+
"e n",
|
| 830 |
+
"a r",
|
| 831 |
+
"t i",
|
| 832 |
+
"a l",
|
| 833 |
+
"t e",
|
| 834 |
+
"i c",
|
| 835 |
+
"i s",
|
| 836 |
+
"i t",
|
| 837 |
+
"s t",
|
| 838 |
+
"e s",
|
| 839 |
+
"e d",
|
| 840 |
+
"f i",
|
| 841 |
+
"f o",
|
| 842 |
+
"c o",
|
| 843 |
+
"c l",
|
| 844 |
+
"t r",
|
| 845 |
+
"l i",
|
| 846 |
+
"l o",
|
| 847 |
+
"t h",
|
| 848 |
+
"n d",
|
| 849 |
+
"n t",
|
| 850 |
+
"r i",
|
| 851 |
+
"r o",
|
| 852 |
+
"l a",
|
| 853 |
+
"m e",
|
| 854 |
+
"p a",
|
| 855 |
+
"n c",
|
| 856 |
+
"p e",
|
| 857 |
+
"e x",
|
| 858 |
+
"u n",
|
| 859 |
+
"n g",
|
| 860 |
+
"p o",
|
| 861 |
+
"a c",
|
| 862 |
+
"m o",
|
| 863 |
+
"s i",
|
| 864 |
+
"\u0120 \u0120",
|
| 865 |
+
"\u0120 t",
|
| 866 |
+
"\u0120 a",
|
| 867 |
+
"\u0120 i",
|
| 868 |
+
"\u0120 s",
|
| 869 |
+
"\u0120 r",
|
| 870 |
+
"\u0120 f",
|
| 871 |
+
"\u0120 c",
|
| 872 |
+
"\u0120 d",
|
| 873 |
+
"\u0120 p",
|
| 874 |
+
"\u0120 m",
|
| 875 |
+
"\u0120 w",
|
| 876 |
+
"\u0120 n",
|
| 877 |
+
"\u0120 b",
|
| 878 |
+
"\u0120 e",
|
| 879 |
+
"\u0120 l",
|
| 880 |
+
"\u0120 g",
|
| 881 |
+
"\u0120 h",
|
| 882 |
+
"\u0120 o",
|
| 883 |
+
"\u0120 v",
|
| 884 |
+
"\u0120 u",
|
| 885 |
+
"\u0120 y",
|
| 886 |
+
"e r r",
|
| 887 |
+
"i ng",
|
| 888 |
+
"t ion",
|
| 889 |
+
"m ent",
|
| 890 |
+
"b le",
|
| 891 |
+
"d e",
|
| 892 |
+
"de f",
|
| 893 |
+
"\u0120d ef",
|
| 894 |
+
"\u0120de f",
|
| 895 |
+
"c la",
|
| 896 |
+
"cla s",
|
| 897 |
+
"clas s",
|
| 898 |
+
"\u0120c lass",
|
| 899 |
+
"i m",
|
| 900 |
+
"im p",
|
| 901 |
+
"imp o",
|
| 902 |
+
"impo r",
|
| 903 |
+
"impor t",
|
| 904 |
+
"\u0120i mport",
|
| 905 |
+
"r et",
|
| 906 |
+
"ret u",
|
| 907 |
+
"retu r",
|
| 908 |
+
"retur n",
|
| 909 |
+
"\u0120r eturn",
|
| 910 |
+
"s el",
|
| 911 |
+
"sel f",
|
| 912 |
+
"\u0120s elf",
|
| 913 |
+
"a s",
|
| 914 |
+
"as y",
|
| 915 |
+
"asy nc",
|
| 916 |
+
"\u0120a sync",
|
| 917 |
+
"a w",
|
| 918 |
+
"aw a",
|
| 919 |
+
"awa i",
|
| 920 |
+
"awai t",
|
| 921 |
+
"\u0120a wait",
|
| 922 |
+
"f un",
|
| 923 |
+
"fun c",
|
| 924 |
+
"func t",
|
| 925 |
+
"funct i",
|
| 926 |
+
"functi on",
|
| 927 |
+
"\u0120f unction",
|
| 928 |
+
"c on",
|
| 929 |
+
"con s",
|
| 930 |
+
"cons t",
|
| 931 |
+
"\u0120c onst",
|
| 932 |
+
"l et",
|
| 933 |
+
"\u0120l et",
|
| 934 |
+
"e x",
|
| 935 |
+
"ex p",
|
| 936 |
+
"exp o",
|
| 937 |
+
"expo r",
|
| 938 |
+
"expor t",
|
| 939 |
+
"\u0120e xport",
|
| 940 |
+
"= =",
|
| 941 |
+
"! =",
|
| 942 |
+
"< =",
|
| 943 |
+
"> =",
|
| 944 |
+
"= >",
|
| 945 |
+
"- >",
|
| 946 |
+
": :",
|
| 947 |
+
"* *",
|
| 948 |
+
"/ /",
|
| 949 |
+
"& &",
|
| 950 |
+
"| |",
|
| 951 |
+
"? ?",
|
| 952 |
+
". .",
|
| 953 |
+
". ..",
|
| 954 |
+
"T r",
|
| 955 |
+
"Tr u",
|
| 956 |
+
"Tru e",
|
| 957 |
+
"\u0120T rue",
|
| 958 |
+
"F al",
|
| 959 |
+
"Fal s",
|
| 960 |
+
"Fals e",
|
| 961 |
+
"\u0120F alse",
|
| 962 |
+
"N on",
|
| 963 |
+
"Non e",
|
| 964 |
+
"\u0120N one",
|
| 965 |
+
"n ul",
|
| 966 |
+
"nul l",
|
| 967 |
+
"\u0120n ull",
|
| 968 |
+
"\u0120\u0120 \u0120\u0120",
|
| 969 |
+
"\u010a \u0120",
|
| 970 |
+
"\u010a\u0120 \u0120",
|
| 971 |
+
"\u010a\u0120\u0120 \u0120\u0120",
|
| 972 |
+
"f n",
|
| 973 |
+
"\u0120f n",
|
| 974 |
+
"p ub",
|
| 975 |
+
"\u0120p ub",
|
| 976 |
+
"i mp",
|
| 977 |
+
"imp l",
|
| 978 |
+
"\u0120i mpl",
|
| 979 |
+
"s tr",
|
| 980 |
+
"str u",
|
| 981 |
+
"stru c",
|
| 982 |
+
"struc t",
|
| 983 |
+
"\u0120s truct",
|
| 984 |
+
"m at",
|
| 985 |
+
"mat ch",
|
| 986 |
+
"\u0120m atch",
|
| 987 |
+
"t rait",
|
| 988 |
+
"\u0120t rait",
|
| 989 |
+
"\u0120\u0120\u0120\u0120 \u0120\u0120\u0120\u0120"
|
| 990 |
+
]
|
| 991 |
+
}
|
| 992 |
+
}
|
tokenizer_config.json
ADDED
|
@@ -0,0 +1,94 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_bos_token": false,
|
| 3 |
+
"add_prefix_space": false,
|
| 4 |
+
"added_tokens_decoder": {
|
| 5 |
+
"151643": {
|
| 6 |
+
"content": "<|endoftext|>",
|
| 7 |
+
"lstrip": false,
|
| 8 |
+
"normalized": false,
|
| 9 |
+
"rstrip": false,
|
| 10 |
+
"single_word": false,
|
| 11 |
+
"special": true
|
| 12 |
+
},
|
| 13 |
+
"151644": {
|
| 14 |
+
"content": "<|im_start|>",
|
| 15 |
+
"lstrip": false,
|
| 16 |
+
"normalized": false,
|
| 17 |
+
"rstrip": false,
|
| 18 |
+
"single_word": false,
|
| 19 |
+
"special": true
|
| 20 |
+
},
|
| 21 |
+
"151645": {
|
| 22 |
+
"content": "<|im_end|>",
|
| 23 |
+
"lstrip": false,
|
| 24 |
+
"normalized": false,
|
| 25 |
+
"rstrip": false,
|
| 26 |
+
"single_word": false,
|
| 27 |
+
"special": true
|
| 28 |
+
},
|
| 29 |
+
"151652": {
|
| 30 |
+
"content": "<|vision_start|>",
|
| 31 |
+
"lstrip": false,
|
| 32 |
+
"normalized": false,
|
| 33 |
+
"rstrip": false,
|
| 34 |
+
"single_word": false,
|
| 35 |
+
"special": true
|
| 36 |
+
},
|
| 37 |
+
"151653": {
|
| 38 |
+
"content": "<|vision_end|>",
|
| 39 |
+
"lstrip": false,
|
| 40 |
+
"normalized": false,
|
| 41 |
+
"rstrip": false,
|
| 42 |
+
"single_word": false,
|
| 43 |
+
"special": true
|
| 44 |
+
},
|
| 45 |
+
"151654": {
|
| 46 |
+
"content": "<|vision_pad|>",
|
| 47 |
+
"lstrip": false,
|
| 48 |
+
"normalized": false,
|
| 49 |
+
"rstrip": false,
|
| 50 |
+
"single_word": false,
|
| 51 |
+
"special": true
|
| 52 |
+
},
|
| 53 |
+
"151655": {
|
| 54 |
+
"content": "<|image_pad|>",
|
| 55 |
+
"lstrip": false,
|
| 56 |
+
"normalized": false,
|
| 57 |
+
"rstrip": false,
|
| 58 |
+
"single_word": false,
|
| 59 |
+
"special": true
|
| 60 |
+
},
|
| 61 |
+
"151656": {
|
| 62 |
+
"content": "<|video_pad|>",
|
| 63 |
+
"lstrip": false,
|
| 64 |
+
"normalized": false,
|
| 65 |
+
"rstrip": false,
|
| 66 |
+
"single_word": false,
|
| 67 |
+
"special": true
|
| 68 |
+
}
|
| 69 |
+
},
|
| 70 |
+
"additional_special_tokens": [
|
| 71 |
+
"<|im_start|>",
|
| 72 |
+
"<|im_end|>",
|
| 73 |
+
"<|vision_start|>",
|
| 74 |
+
"<|vision_end|>",
|
| 75 |
+
"<|vision_pad|>",
|
| 76 |
+
"<|image_pad|>",
|
| 77 |
+
"<|video_pad|>"
|
| 78 |
+
],
|
| 79 |
+
"bos_token": null,
|
| 80 |
+
"chat_template": "{%- if messages[0]['role'] == 'system' %}{%- set system_message = messages[0]['content'] %}{%- set loop_messages = messages[1:] %}{%- else %}{%- set system_message = 'You are Verus, a helpful multimodal coding assistant. You specialize in converting UI mockups, wireframes, and architecture diagrams into production-ready code.' %}{%- set loop_messages = messages %}{%- endif %}{{- '<|im_start|>system\\n' + system_message + '<|im_end|>\\n' }}{%- for message in loop_messages %}{%- if message['role'] == 'user' %}{{- '<|im_start|>user\\n' }}{%- if message['content'] is iterable and message['content'] is not string %}{%- for item in message['content'] %}{%- if item['type'] == 'image' %}{{- '<|vision_start|><|image_pad|><|vision_end|>' }}{%- elif item['type'] == 'text' %}{{- item['text'] }}{%- endif %}{%- endfor %}{%- else %}{{- message['content'] }}{%- endif %}{{- '<|im_end|>\\n' }}{%- elif message['role'] == 'assistant' %}{{- '<|im_start|>assistant\\n' }}{%- if message['content'] is not none %}{{- message['content'] }}{%- endif %}{%- if not loop.last or not add_generation_prompt %}{{- '<|im_end|>\\n' }}{%- endif %}{%- endif %}{%- endfor %}{%- if add_generation_prompt %}{{- '<|im_start|>assistant\\n' }}{%- endif %}",
|
| 81 |
+
"clean_up_tokenization_spaces": false,
|
| 82 |
+
"eos_token": "<|im_end|>",
|
| 83 |
+
"errors": "replace",
|
| 84 |
+
"model_max_length": 125000,
|
| 85 |
+
"pad_token": "<|endoftext|>",
|
| 86 |
+
"padding_side": "left",
|
| 87 |
+
"split_special_tokens": false,
|
| 88 |
+
"tokenizer_class": "Qwen2Tokenizer",
|
| 89 |
+
"unk_token": null,
|
| 90 |
+
"image_token": "<|image_pad|>",
|
| 91 |
+
"video_token": "<|video_pad|>",
|
| 92 |
+
"vision_start_token": "<|vision_start|>",
|
| 93 |
+
"vision_end_token": "<|vision_end|>"
|
| 94 |
+
}
|
train.py
ADDED
|
@@ -0,0 +1,450 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
| 1 |
+
# ╔══════════════════════════════════════════════════════════════════════════════╗
|
| 2 |
+
# ║ Verus-4B — Fine-Tune Training Script (Run 2) ║
|
| 3 |
+
# ║ 8F-ai | Apache 2.0 ║
|
| 4 |
+
# ╠══════════════════════════════════════════════════════════════════════════════╣
|
| 5 |
+
# ║ Base model : ./Verus-4b (your Run 1 local output) ║
|
| 6 |
+
# ║ Datasets : m-a-p/CodeFeedback-Filtered-Instruction (primary coding) ║
|
| 7 |
+
# ║ HuggingFaceH4/ultrachat_200k (general) ║
|
| 8 |
+
# ║ ise-uiuc/Magicoder-OSS-Instruct-75K (extra coding) ║
|
| 9 |
+
# ║ Target HW : Lightning AI H100 (80GB VRAM) ║
|
| 10 |
+
# ║ Time goal : ~30 minutes ║
|
| 11 |
+
# ║ Output : ./Verus-4b-r2/ ║
|
| 12 |
+
# ╠══════════════════════════════════════════════════════════════════════════════╣
|
| 13 |
+
# ║ Quickstart: ║
|
| 14 |
+
# ║ pip install git+https://github.com/huggingface/transformers.git ║
|
| 15 |
+
# ║ pip install datasets peft safetensors accelerate ║
|
| 16 |
+
# ║ export HF_TOKEN=hf_xxx ║
|
| 17 |
+
# ║ python train.py ║
|
| 18 |
+
# ╚══════════════════════════════════════════════════════════════════════════════╝
|
| 19 |
+
|
| 20 |
+
import os, re, sys, json, time, logging, warnings, threading
|
| 21 |
+
from pathlib import Path
|
| 22 |
+
from datetime import datetime, timezone
|
| 23 |
+
|
| 24 |
+
warnings.filterwarnings("ignore", category=UserWarning)
|
| 25 |
+
os.environ["TOKENIZERS_PARALLELISM"] = "false"
|
| 26 |
+
os.environ["PYTORCH_ALLOC_CONF"] = "expandable_segments:True"
|
| 27 |
+
os.environ["TORCHDYNAMO_DISABLE"] = "1"
|
| 28 |
+
|
| 29 |
+
# ── HF auth ───────────────────────────────────────────────────────────────────
|
| 30 |
+
_hf_token = os.environ.get("HF_TOKEN", "").strip()
|
| 31 |
+
if _hf_token:
|
| 32 |
+
try:
|
| 33 |
+
from huggingface_hub import login as _hf_login
|
| 34 |
+
_hf_login(token=_hf_token, add_to_git_credential=False)
|
| 35 |
+
print(f"[HF] Logged in ({_hf_token[:8]}{'*' * max(0, len(_hf_token)-8)})")
|
| 36 |
+
except Exception as e:
|
| 37 |
+
print(f"[HF] Login skipped: {e}")
|
| 38 |
+
else:
|
| 39 |
+
print("[HF] HF_TOKEN not set — export HF_TOKEN=hf_xxx")
|
| 40 |
+
|
| 41 |
+
import torch
|
| 42 |
+
from torch.utils.data import Dataset, DataLoader, ConcatDataset
|
| 43 |
+
from transformers import (
|
| 44 |
+
AutoTokenizer, AutoModelForCausalLM, set_seed,
|
| 45 |
+
get_cosine_schedule_with_warmup,
|
| 46 |
+
)
|
| 47 |
+
from datasets import load_dataset
|
| 48 |
+
from safetensors.torch import save_file
|
| 49 |
+
|
| 50 |
+
try:
|
| 51 |
+
from peft import LoraConfig, TaskType, get_peft_model
|
| 52 |
+
except ImportError:
|
| 53 |
+
print("[ERR] pip install peft"); sys.exit(1)
|
| 54 |
+
|
| 55 |
+
# ── Device ────────────────────────────────────────────────────────────────────
|
| 56 |
+
if torch.cuda.is_available():
|
| 57 |
+
DEVICE = torch.device("cuda")
|
| 58 |
+
gpu = torch.cuda.get_device_name(0)
|
| 59 |
+
vram = torch.cuda.get_device_properties(0).total_memory / 1e9
|
| 60 |
+
print(f"[GPU] {gpu} — {vram:.1f} GB VRAM")
|
| 61 |
+
else:
|
| 62 |
+
DEVICE = torch.device("cpu")
|
| 63 |
+
print("[WARN] No GPU found!")
|
| 64 |
+
|
| 65 |
+
# ══════════════════════════════════════════════════════════════════════════════
|
| 66 |
+
# CONFIG — 4B model on H100 80GB, target ~30 min
|
| 67 |
+
#
|
| 68 |
+
# Memory estimate:
|
| 69 |
+
# 4B params × 2 bytes (bf16) = ~8 GB model
|
| 70 |
+
# LoRA r=32 gradients + optimizer = ~12 GB
|
| 71 |
+
# Activations (batch 4, seq 512) = ~18 GB
|
| 72 |
+
# Total = ~38 GB ← well within 80GB
|
| 73 |
+
# ══════════════════════════════════════════════════════════════════════════════
|
| 74 |
+
CFG = {
|
| 75 |
+
"model_id": "8F-ai/Verus-4B",
|
| 76 |
+
"base_model": "./Verus-4b", # ← local Run 1 output
|
| 77 |
+
|
| 78 |
+
# ── Datasets ────────────────────────────────────────────────────────────
|
| 79 |
+
"ultra_samples": 2000, # UltraChat general conversation
|
| 80 |
+
"code_samples": 8000, # CodeFeedback coding
|
| 81 |
+
"magic_samples": 4000, # Magicoder extra coding
|
| 82 |
+
|
| 83 |
+
# ── Output ──────────────────────────────────────────────────────────────
|
| 84 |
+
"final_dir": "./Verus-4b-r2",
|
| 85 |
+
|
| 86 |
+
# ── Training ────────────────────────────────────────────────────────────
|
| 87 |
+
"total_budget_sec": 1800, # 30 min hard limit
|
| 88 |
+
"save_reserve_sec": 400, # ~7 min for 4B merge+save
|
| 89 |
+
|
| 90 |
+
"max_seq_len": 512, # stable, no OOM crashes
|
| 91 |
+
"per_device_batch": 4,
|
| 92 |
+
"grad_accum_steps": 8, # effective batch = 32
|
| 93 |
+
"learning_rate": 5e-5, # lower lr for run 2 — already a tuned model
|
| 94 |
+
"weight_decay": 0.01,
|
| 95 |
+
"max_grad_norm": 1.0,
|
| 96 |
+
"warmup_steps": 80, # shorter warmup for shorter run
|
| 97 |
+
"max_steps": 2500,
|
| 98 |
+
|
| 99 |
+
# ── LoRA ────────────────────────────────────────────────────────────────
|
| 100 |
+
"lora_r": 32,
|
| 101 |
+
"lora_alpha": 64,
|
| 102 |
+
"lora_dropout": 0.05,
|
| 103 |
+
"lora_targets": ["q_proj", "k_proj", "v_proj", "o_proj",
|
| 104 |
+
"gate_proj", "up_proj", "down_proj"],
|
| 105 |
+
|
| 106 |
+
"seed": 42,
|
| 107 |
+
"system_prompt": (
|
| 108 |
+
"You are Verus, a coding assistant made by 8F-ai. "
|
| 109 |
+
"You help with coding tasks and keep responses focused and clean. "
|
| 110 |
+
"For greetings respond briefly and redirect to coding."
|
| 111 |
+
),
|
| 112 |
+
}
|
| 113 |
+
|
| 114 |
+
logging.basicConfig(
|
| 115 |
+
level=logging.INFO,
|
| 116 |
+
format="%(asctime)s %(levelname)-8s %(message)s",
|
| 117 |
+
datefmt="%H:%M:%S",
|
| 118 |
+
handlers=[logging.StreamHandler(sys.stdout)],
|
| 119 |
+
)
|
| 120 |
+
log = logging.getLogger("verus")
|
| 121 |
+
set_seed(CFG["seed"])
|
| 122 |
+
|
| 123 |
+
# ══════════════════════════════════════════════════════════════════════════════
|
| 124 |
+
# HEARTBEAT
|
| 125 |
+
# ══════════════════════════════════════════════════════════════════════════════
|
| 126 |
+
def _start_heartbeat(interval: int = 30):
|
| 127 |
+
def _beat():
|
| 128 |
+
while True:
|
| 129 |
+
print("[HEARTBEAT] alive …", flush=True)
|
| 130 |
+
time.sleep(interval)
|
| 131 |
+
threading.Thread(target=_beat, daemon=True).start()
|
| 132 |
+
|
| 133 |
+
# ══════════════════════════════════════════════════════════════════════════════
|
| 134 |
+
# DATASETS
|
| 135 |
+
# ══════════════════════════════════════════════════════════════════════════════
|
| 136 |
+
def _chatml(system: str, user: str, assistant: str) -> str:
|
| 137 |
+
return (
|
| 138 |
+
f"<|im_start|>system\n{system}<|im_end|>\n"
|
| 139 |
+
f"<|im_start|>user\n{user.strip()}<|im_end|>\n"
|
| 140 |
+
f"<|im_start|>assistant\n{assistant.strip()}<|im_end|>"
|
| 141 |
+
)
|
| 142 |
+
|
| 143 |
+
class TokenizedDataset(Dataset):
|
| 144 |
+
def __init__(self, texts, tokenizer, max_len):
|
| 145 |
+
log.info(f" Tokenising {len(texts):,} examples (max_len={max_len}) …")
|
| 146 |
+
enc = tokenizer(
|
| 147 |
+
texts,
|
| 148 |
+
max_length=max_len,
|
| 149 |
+
padding="max_length",
|
| 150 |
+
truncation=True,
|
| 151 |
+
return_attention_mask=True,
|
| 152 |
+
return_tensors=None,
|
| 153 |
+
)
|
| 154 |
+
pad = tokenizer.pad_token_id or 0
|
| 155 |
+
self.ids = enc["input_ids"]
|
| 156 |
+
self.mask = enc["attention_mask"]
|
| 157 |
+
self.lbls = [[(t if t != pad else -100) for t in s] for s in enc["input_ids"]]
|
| 158 |
+
|
| 159 |
+
def __len__(self): return len(self.ids)
|
| 160 |
+
def __getitem__(self, i):
|
| 161 |
+
return {
|
| 162 |
+
"input_ids": torch.tensor(self.ids[i], dtype=torch.long),
|
| 163 |
+
"attention_mask": torch.tensor(self.mask[i], dtype=torch.long),
|
| 164 |
+
"labels": torch.tensor(self.lbls[i], dtype=torch.long),
|
| 165 |
+
}
|
| 166 |
+
|
| 167 |
+
def load_ultrachat_dataset(tokenizer, cfg):
|
| 168 |
+
log.info("Loading HuggingFaceH4/ultrachat_200k …")
|
| 169 |
+
raw = load_dataset("HuggingFaceH4/ultrachat_200k", split="train_sft")
|
| 170 |
+
raw = raw.select(range(min(cfg["ultra_samples"], len(raw))))
|
| 171 |
+
texts = []
|
| 172 |
+
for ex in raw:
|
| 173 |
+
messages = ex.get("messages", [])
|
| 174 |
+
user_msg = next((m["content"] for m in messages if m["role"] == "user"), "")
|
| 175 |
+
asst_msg = next((m["content"] for m in messages if m["role"] == "assistant"), "")
|
| 176 |
+
if user_msg and asst_msg:
|
| 177 |
+
texts.append(_chatml(cfg["system_prompt"], user_msg, asst_msg))
|
| 178 |
+
log.info(f" {len(texts):,} ultrachat examples ready.")
|
| 179 |
+
return TokenizedDataset(texts, tokenizer, cfg["max_seq_len"])
|
| 180 |
+
|
| 181 |
+
def load_codefeedback_dataset(tokenizer, cfg):
|
| 182 |
+
log.info("Loading m-a-p/CodeFeedback-Filtered-Instruction …")
|
| 183 |
+
raw = load_dataset("m-a-p/CodeFeedback-Filtered-Instruction", split="train")
|
| 184 |
+
raw = raw.select(range(min(cfg["code_samples"], len(raw))))
|
| 185 |
+
texts = []
|
| 186 |
+
for ex in raw:
|
| 187 |
+
inst = ex.get("query", "").strip()
|
| 188 |
+
out = ex.get("answer", "").strip()
|
| 189 |
+
if inst and out:
|
| 190 |
+
texts.append(_chatml(cfg["system_prompt"], inst, out))
|
| 191 |
+
log.info(f" {len(texts):,} CodeFeedback examples ready.")
|
| 192 |
+
return TokenizedDataset(texts, tokenizer, cfg["max_seq_len"])
|
| 193 |
+
|
| 194 |
+
def load_magicoder_dataset(tokenizer, cfg):
|
| 195 |
+
log.info("Loading ise-uiuc/Magicoder-OSS-Instruct-75K …")
|
| 196 |
+
raw = load_dataset("ise-uiuc/Magicoder-OSS-Instruct-75K", split="train")
|
| 197 |
+
raw = raw.select(range(min(cfg["magic_samples"], len(raw))))
|
| 198 |
+
texts = []
|
| 199 |
+
for ex in raw:
|
| 200 |
+
inst = ex.get("problem", "").strip()
|
| 201 |
+
out = ex.get("solution", "").strip()
|
| 202 |
+
if inst and out:
|
| 203 |
+
texts.append(_chatml(cfg["system_prompt"], inst, out))
|
| 204 |
+
log.info(f" {len(texts):,} Magicoder examples ready.")
|
| 205 |
+
return TokenizedDataset(texts, tokenizer, cfg["max_seq_len"])
|
| 206 |
+
|
| 207 |
+
# ══════════════════════════════════════════════════════════════════════════════
|
| 208 |
+
# MODEL
|
| 209 |
+
# ══════════════════════════════════════════════════════════════════════════════
|
| 210 |
+
def load_model(cfg):
|
| 211 |
+
base = cfg["base_model"]
|
| 212 |
+
log.info(f"Loading tokenizer from {base} …")
|
| 213 |
+
tok = AutoTokenizer.from_pretrained(base, padding_side="right", use_fast=True)
|
| 214 |
+
if tok.pad_token_id is None:
|
| 215 |
+
tok.pad_token_id = tok.eos_token_id
|
| 216 |
+
|
| 217 |
+
log.info(f"Loading model (bfloat16) …")
|
| 218 |
+
model = AutoModelForCausalLM.from_pretrained(
|
| 219 |
+
base,
|
| 220 |
+
torch_dtype=torch.bfloat16,
|
| 221 |
+
low_cpu_mem_usage=True,
|
| 222 |
+
)
|
| 223 |
+
model.config.use_cache = False
|
| 224 |
+
|
| 225 |
+
log.info("Attaching LoRA …")
|
| 226 |
+
model = get_peft_model(model, LoraConfig(
|
| 227 |
+
task_type=TaskType.CAUSAL_LM,
|
| 228 |
+
r=cfg["lora_r"],
|
| 229 |
+
lora_alpha=cfg["lora_alpha"],
|
| 230 |
+
lora_dropout=cfg["lora_dropout"],
|
| 231 |
+
target_modules=cfg["lora_targets"],
|
| 232 |
+
bias="none",
|
| 233 |
+
inference_mode=False,
|
| 234 |
+
))
|
| 235 |
+
model.print_trainable_parameters()
|
| 236 |
+
return model, tok
|
| 237 |
+
|
| 238 |
+
# ══════════════════════════════════════════════════════════════════════════════
|
| 239 |
+
# SAVE — 2-shard safetensors (HuggingFace standard format)
|
| 240 |
+
# ══════════════════════════════════════════════════════════════════════════════
|
| 241 |
+
def _save_checkpoint(peft_model, tokenizer, cfg, step, t0):
|
| 242 |
+
out = Path(cfg["final_dir"]) / f"checkpoint-{step}"
|
| 243 |
+
out.mkdir(parents=True, exist_ok=True)
|
| 244 |
+
peft_model.save_pretrained(str(out))
|
| 245 |
+
tokenizer.save_pretrained(str(out))
|
| 246 |
+
log.info(f" ✅ Checkpoint saved → {out}/")
|
| 247 |
+
|
| 248 |
+
def save_model(peft_model, tokenizer, cfg, t0):
|
| 249 |
+
out = Path(cfg["final_dir"])
|
| 250 |
+
out.mkdir(parents=True, exist_ok=True)
|
| 251 |
+
|
| 252 |
+
log.info("Merging LoRA into base weights …")
|
| 253 |
+
merged = peft_model.merge_and_unload()
|
| 254 |
+
merged.eval()
|
| 255 |
+
|
| 256 |
+
log.info("Collecting state dict …")
|
| 257 |
+
sd = {k: v.detach().to("cpu", dtype=torch.bfloat16).contiguous()
|
| 258 |
+
for k, v in merged.named_parameters()}
|
| 259 |
+
sd.update({k: v.detach().to("cpu").contiguous()
|
| 260 |
+
for k, v in merged.named_buffers()})
|
| 261 |
+
|
| 262 |
+
meta = {
|
| 263 |
+
"format": "pt",
|
| 264 |
+
"model_id": cfg["model_id"],
|
| 265 |
+
"base_model": cfg["base_model"],
|
| 266 |
+
"datasets": "UltraChat + CodeFeedback + Magicoder",
|
| 267 |
+
"created_at": datetime.now(timezone.utc).isoformat(),
|
| 268 |
+
"train_time": f"{(time.time()-t0)/60:.1f} min",
|
| 269 |
+
"hardware": "Lightning AI H100 80GB",
|
| 270 |
+
}
|
| 271 |
+
|
| 272 |
+
# ── Split state dict into 2 shards ──────────────────────────────────────
|
| 273 |
+
log.info("Splitting into 2 shards …")
|
| 274 |
+
all_keys = list(sd.keys())
|
| 275 |
+
mid = len(all_keys) // 2
|
| 276 |
+
shard1_sd = {k: sd[k] for k in all_keys[:mid]}
|
| 277 |
+
shard2_sd = {k: sd[k] for k in all_keys[mid:]}
|
| 278 |
+
|
| 279 |
+
shard1_name = "model-00001-of-00002.safetensors"
|
| 280 |
+
shard2_name = "model-00002-of-00002.safetensors"
|
| 281 |
+
shard1_path = out / shard1_name
|
| 282 |
+
shard2_path = out / shard2_name
|
| 283 |
+
|
| 284 |
+
log.info(f"Writing {shard1_name} ({len(shard1_sd)} tensors) …")
|
| 285 |
+
save_file(shard1_sd, str(shard1_path), metadata=meta)
|
| 286 |
+
size1 = shard1_path.stat().st_size
|
| 287 |
+
log.info(f" {size1/1e9:.3f} GB written.")
|
| 288 |
+
|
| 289 |
+
log.info(f"Writing {shard2_name} ({len(shard2_sd)} tensors) …")
|
| 290 |
+
save_file(shard2_sd, str(shard2_path), metadata=meta)
|
| 291 |
+
size2 = shard2_path.stat().st_size
|
| 292 |
+
log.info(f" {size2/1e9:.3f} GB written.")
|
| 293 |
+
|
| 294 |
+
total_size = size1 + size2
|
| 295 |
+
|
| 296 |
+
# ── Write the index file ─────────────────────────────────────────────────
|
| 297 |
+
weight_map = {}
|
| 298 |
+
for k in all_keys[:mid]:
|
| 299 |
+
weight_map[k] = shard1_name
|
| 300 |
+
for k in all_keys[mid:]:
|
| 301 |
+
weight_map[k] = shard2_name
|
| 302 |
+
|
| 303 |
+
index = {
|
| 304 |
+
"metadata": {
|
| 305 |
+
**meta,
|
| 306 |
+
"total_size": total_size,
|
| 307 |
+
"num_shards": 2,
|
| 308 |
+
},
|
| 309 |
+
"weight_map": weight_map,
|
| 310 |
+
}
|
| 311 |
+
index_path = out / "model.safetensors.index.json"
|
| 312 |
+
with open(index_path, "w") as f:
|
| 313 |
+
json.dump(index, f, indent=2)
|
| 314 |
+
log.info(f" Index written → {index_path}")
|
| 315 |
+
log.info(f" Total size: {total_size/1e9:.3f} GB across 2 shards")
|
| 316 |
+
|
| 317 |
+
# ── Save tokenizer + config ──────────────────────────────────────────────
|
| 318 |
+
tokenizer.save_pretrained(str(out))
|
| 319 |
+
merged.config.save_pretrained(str(out))
|
| 320 |
+
|
| 321 |
+
cfg_p = out / "config.json"
|
| 322 |
+
if cfg_p.exists():
|
| 323 |
+
with open(cfg_p) as f: doc = json.load(f)
|
| 324 |
+
doc["_name_or_path"] = cfg["model_id"]
|
| 325 |
+
with open(cfg_p, "w") as f: json.dump(doc, f, indent=2)
|
| 326 |
+
|
| 327 |
+
log.info(f"All files saved to {out}/")
|
| 328 |
+
log.info(f" {shard1_name}")
|
| 329 |
+
log.info(f" {shard2_name}")
|
| 330 |
+
log.info(f" model.safetensors.index.json")
|
| 331 |
+
|
| 332 |
+
# ══════════════════════════════════════════════════════════════════════════════
|
| 333 |
+
# TRAINING LOOP
|
| 334 |
+
# ══════════════════════════════════════════════════════════════════════════════
|
| 335 |
+
def train_loop(model, dataset, cfg, t0, tokenizer):
|
| 336 |
+
deadline = t0 + cfg["total_budget_sec"] - cfg["save_reserve_sec"]
|
| 337 |
+
loader = DataLoader(
|
| 338 |
+
dataset,
|
| 339 |
+
batch_size=cfg["per_device_batch"],
|
| 340 |
+
shuffle=True,
|
| 341 |
+
drop_last=True,
|
| 342 |
+
num_workers=4,
|
| 343 |
+
pin_memory=True,
|
| 344 |
+
)
|
| 345 |
+
opt = torch.optim.AdamW(
|
| 346 |
+
model.parameters(),
|
| 347 |
+
lr=cfg["learning_rate"],
|
| 348 |
+
weight_decay=cfg["weight_decay"],
|
| 349 |
+
)
|
| 350 |
+
sched = get_cosine_schedule_with_warmup(
|
| 351 |
+
opt,
|
| 352 |
+
num_warmup_steps=cfg["warmup_steps"],
|
| 353 |
+
num_training_steps=cfg["max_steps"],
|
| 354 |
+
)
|
| 355 |
+
|
| 356 |
+
model.to(DEVICE)
|
| 357 |
+
model.train()
|
| 358 |
+
opt.zero_grad()
|
| 359 |
+
|
| 360 |
+
step = 0; total_loss = 0.0
|
| 361 |
+
log.info("─" * 68)
|
| 362 |
+
log.info("Training started …")
|
| 363 |
+
log.info("─" * 68)
|
| 364 |
+
|
| 365 |
+
for _ in range(9999):
|
| 366 |
+
for batch in loader:
|
| 367 |
+
if step >= cfg["max_steps"] or time.time() >= deadline:
|
| 368 |
+
break
|
| 369 |
+
|
| 370 |
+
ids = batch["input_ids"].to(DEVICE, non_blocking=True)
|
| 371 |
+
mask = batch["attention_mask"].to(DEVICE, non_blocking=True)
|
| 372 |
+
lbls = batch["labels"].to(DEVICE, non_blocking=True)
|
| 373 |
+
|
| 374 |
+
with torch.amp.autocast("cuda", dtype=torch.bfloat16):
|
| 375 |
+
loss = model(input_ids=ids, attention_mask=mask, labels=lbls).loss
|
| 376 |
+
|
| 377 |
+
(loss / cfg["grad_accum_steps"]).backward()
|
| 378 |
+
total_loss += loss.item()
|
| 379 |
+
|
| 380 |
+
if (step + 1) % cfg["grad_accum_steps"] == 0:
|
| 381 |
+
torch.nn.utils.clip_grad_norm_(
|
| 382 |
+
model.parameters(), cfg["max_grad_norm"]
|
| 383 |
+
)
|
| 384 |
+
opt.step(); sched.step(); opt.zero_grad()
|
| 385 |
+
|
| 386 |
+
step += 1
|
| 387 |
+
|
| 388 |
+
if step % 50 == 0 or step == 1:
|
| 389 |
+
avg = total_loss / step
|
| 390 |
+
lr_ = sched.get_last_lr()[0]
|
| 391 |
+
mins = (time.time() - t0) / 60
|
| 392 |
+
remaining = (deadline - time.time()) / 60
|
| 393 |
+
log.info(
|
| 394 |
+
f" step {step:>5}/{cfg['max_steps']} "
|
| 395 |
+
f"loss {avg:.4f} lr {lr_:.2e} "
|
| 396 |
+
f"{mins:.1f}min ({remaining:.0f}min left)"
|
| 397 |
+
)
|
| 398 |
+
|
| 399 |
+
if step % 1000 == 0:
|
| 400 |
+
log.info(f"Saving checkpoint at step {step} …")
|
| 401 |
+
_save_checkpoint(model, tokenizer, cfg, step, t0)
|
| 402 |
+
|
| 403 |
+
if step >= cfg["max_steps"] or time.time() >= deadline:
|
| 404 |
+
break
|
| 405 |
+
|
| 406 |
+
avg = total_loss / max(step, 1)
|
| 407 |
+
log.info(f"Training done — steps: {step} avg loss: {avg:.4f} time: {(time.time()-t0)/60:.1f} min")
|
| 408 |
+
return step, avg
|
| 409 |
+
|
| 410 |
+
# ══════════════════════════════════════════════════════════════════════════════
|
| 411 |
+
# MAIN
|
| 412 |
+
# ══════════════════════════════════════════════════════════════════════════════
|
| 413 |
+
def main():
|
| 414 |
+
t0 = time.time()
|
| 415 |
+
_start_heartbeat(30)
|
| 416 |
+
|
| 417 |
+
log.info("=" * 68)
|
| 418 |
+
log.info(" Verus-4b Run 2 | 8F-ai | H100 Run")
|
| 419 |
+
log.info(f" Base : {CFG['base_model']}")
|
| 420 |
+
log.info(f" Device : {DEVICE}")
|
| 421 |
+
log.info(f" Data : {CFG['ultra_samples']} ultrachat + {CFG['code_samples']} CodeFeedback + {CFG['magic_samples']} Magicoder")
|
| 422 |
+
log.info(f" seq : {CFG['max_seq_len']} batch: {CFG['per_device_batch']} accum: {CFG['grad_accum_steps']} steps: {CFG['max_steps']}")
|
| 423 |
+
log.info(f" LoRA : r={CFG['lora_r']} alpha={CFG['lora_alpha']} targets={len(CFG['lora_targets'])} modules")
|
| 424 |
+
log.info(f" Budget : {CFG['total_budget_sec']//60} min (checkpoints every 1000 steps)")
|
| 425 |
+
log.info("=" * 68)
|
| 426 |
+
|
| 427 |
+
model, tok = load_model(CFG)
|
| 428 |
+
|
| 429 |
+
ultra_ds = load_ultrachat_dataset(tok, CFG)
|
| 430 |
+
code_ds = load_codefeedback_dataset(tok, CFG)
|
| 431 |
+
magic_ds = load_magicoder_dataset(tok, CFG)
|
| 432 |
+
mixed = ConcatDataset([ultra_ds, code_ds, magic_ds])
|
| 433 |
+
log.info(f"Mixed dataset: {len(mixed):,} total ({len(ultra_ds):,} ultrachat + {len(code_ds):,} codefeedback + {len(magic_ds):,} magic)")
|
| 434 |
+
|
| 435 |
+
steps, loss = train_loop(model, mixed, CFG, t0, tok)
|
| 436 |
+
save_model(model, tok, CFG, t0)
|
| 437 |
+
|
| 438 |
+
out = Path(CFG["final_dir"])
|
| 439 |
+
s1 = (out / "model-00001-of-00002.safetensors")
|
| 440 |
+
s2 = (out / "model-00002-of-00002.safetensors")
|
| 441 |
+
size = (s1.stat().st_size if s1.exists() else 0) + (s2.stat().st_size if s2.exists() else 0)
|
| 442 |
+
|
| 443 |
+
log.info("=" * 68)
|
| 444 |
+
log.info(" DONE")
|
| 445 |
+
log.info(f" Time : {(time.time()-t0)/60:.1f} min | Steps: {steps} | Loss: {loss:.4f}")
|
| 446 |
+
log.info(f" Size : {size/1e9:.3f} GB across 2 shards → {CFG['final_dir']}/")
|
| 447 |
+
log.info("=" * 68)
|
| 448 |
+
|
| 449 |
+
if __name__ == "__main__":
|
| 450 |
+
main()
|
upload_to_hf.py
ADDED
|
@@ -0,0 +1,30 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
import os
|
| 2 |
+
from huggingface_hub import HfApi
|
| 3 |
+
|
| 4 |
+
def upload_folder_to_hf():
|
| 5 |
+
token = os.getenv("HF_TOKEN")
|
| 6 |
+
if not token:
|
| 7 |
+
print("Error: Run 'export HF_TOKEN=your_token_here' first.")
|
| 8 |
+
return
|
| 9 |
+
|
| 10 |
+
api = HfApi()
|
| 11 |
+
|
| 12 |
+
# "." means "upload everything in the folder I am currently in"
|
| 13 |
+
local_path = "."
|
| 14 |
+
repo_id = "8F-ai/Verus-4B"
|
| 15 |
+
|
| 16 |
+
print(f"Starting upload from current directory to {repo_id}...")
|
| 17 |
+
|
| 18 |
+
try:
|
| 19 |
+
api.upload_folder(
|
| 20 |
+
folder_path=local_path,
|
| 21 |
+
repo_id=repo_id,
|
| 22 |
+
repo_type="model",
|
| 23 |
+
token=token
|
| 24 |
+
)
|
| 25 |
+
print("Upload successful!")
|
| 26 |
+
except Exception as e:
|
| 27 |
+
print(f"An error occurred: {e}")
|
| 28 |
+
|
| 29 |
+
if __name__ == "__main__":
|
| 30 |
+
upload_folder_to_hf()
|
video_preprocessor_config.json
ADDED
|
@@ -0,0 +1,6 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"processor_class": "Qwen2_5_VLProcessor",
|
| 3 |
+
"video_processor_type": "Qwen2VLVideoProcessor",
|
| 4 |
+
"temporal_patch_size": 2,
|
| 5 |
+
"note": "Placeholder scaffold. Replace with the actual Verus-4B video preprocessor config when available."
|
| 6 |
+
}
|
vocab.json
ADDED
|
@@ -0,0 +1,858 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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| 1 |
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{
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| 2 |
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| 3 |
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| 4 |
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| 5 |
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| 6 |
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| 7 |
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| 18 |
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| 19 |
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| 28 |
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| 29 |
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| 30 |
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| 31 |
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| 32 |
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| 33 |
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| 34 |
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| 35 |
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| 36 |
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| 37 |
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">": 34,
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| 38 |
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| 39 |
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| 40 |
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| 57 |
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| 58 |
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| 59 |
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| 60 |
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| 61 |
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| 62 |
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| 63 |
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| 64 |
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| 65 |
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| 67 |
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| 70 |
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| 72 |
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| 73 |
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| 76 |
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| 77 |
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| 78 |
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| 79 |
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| 80 |
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