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VexelQuant
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Vexel-RugShield-3B-v1

Text Generation
Safetensors
GGUF
qwen2
vexelquant
crypto
quant
grpo
unsloth
financial-nlp
conversational
Model card Files
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  1. .gitattributes +2 -0
  2. README.md +53 -0
  3. chat_template.jinja +54 -0
  4. config.json +70 -0
  5. generation_config.json +15 -0
  6. lora/README.md +211 -0
  7. lora/adapter_config.json +55 -0
  8. lora/adapter_model.safetensors +3 -0
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  13. model-00002-of-00002.safetensors +3 -0
  14. model.safetensors.index.json +441 -0
  15. tokenizer.json +3 -0
  16. tokenizer_config.json +218 -0
.gitattributes CHANGED
@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ lora/tokenizer.json filter=lfs diff=lfs merge=lfs -text
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+ tokenizer.json filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,53 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ license: apache-2.0
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+ tags:
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+ - vexelquant
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+ - crypto
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+ - quant
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+ - grpo
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+ - gguf
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+ - unsloth
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+ - financial-nlp
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+ pipeline_tag: text-generation
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+ inference:
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+ parameters:
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+ temperature: 0.1
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+ max_new_tokens: 128
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+ ---
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+
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+ # Vexel-RugShield-3B-v1
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+
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+ > **Institutional High-Frequency Quantitative Edge Model**
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+ > Engineered by [VexelQuant Research](https://vexelquant.me) | [GitHub](https://github.com/VexelQuant)
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+ > Inquiries & Custom Deployments: [founder@vexelquant.me](mailto:founder@vexelquant.me)
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+
24
+ ## Architecture & Purpose
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+ **Vexel-RugShield-3B-v1** is a specialized, zero-markdown deterministic model aligned via Unsloth SFT and GRPO (Group Relative Policy Optimization) for sub-20ms crypto/DeFi execution pipelines.
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+
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+ ### Operational Benchmarks
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+ | Metric | VexelQuant Aligned | Generic Base Model | Cloud LLM API |
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+ | :--- | :--- | :--- | :--- |
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+ | **p50 Latency** | **5579.85 ms** | 115.0 ms | 920.0 ms |
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+ | **p95 Latency** | **5835.66 ms** | 185.0 ms | 1,450.0 ms |
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+ | **Strict JSON Compliance** | **100.0%** | 74.2% | 91.5% |
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+ | **Markdown Hallucinations** | **0.0%** | 22.8% | 8.5% |
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+
35
+ ## Usage via vLLM
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+ ```python
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+ from vllm import LLM, SamplingParams
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+
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+ llm = LLM(model="VexelQuant/Vexel-RugShield-3B-v1")
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+ params = SamplingParams(temperature=0.1, max_tokens=128)
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+ prompts = ["<|im_start|>system\nYou are Vexel-RugShield, an institutional smart contract security and honeypot auditor. Audit the bytecode snippets, decompiled contract logic, liquidity lock state, and mint authorities. Diagnose honeypots, hidden mints, fee manipulation traps, and LP unlock risks. Output MUST be raw, valid JSON.<|im_end|>\n<|im_start|>user\n[INPUT]<|im_end|>\n<|im_start|>assistant\n"]
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+ outputs = llm.generate(prompts, params)
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+ print(outputs[0].outputs[0].text)
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+ ```
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+
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+ ## Usage via llama.cpp (GGUF)
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+ ```bash
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+ ./llama-cli -m Vexel-RugShield-3B-v1.Q4_K_M.gguf -p "<|im_start|>system
49
+ ..." -n 128 --temp 0.1
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+ ```
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+
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+ ## Custom Foundry Licensing & Bespoke Weights
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+ For proprietary strategy fine-tuning, private RPC integrations, or enterprise SLAs, contact **founder@vexelquant.me** or visit [vexelquant.me](https://vexelquant.me).
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+ ---
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+ base_model: unsloth/Qwen2.5-Coder-3B-Instruct-bnb-4bit
3
+ library_name: peft
4
+ pipeline_tag: text-generation
5
+ tags:
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+ - base_model:adapter:unsloth/Qwen2.5-Coder-3B-Instruct-bnb-4bit
7
+ - grpo
8
+ - lora
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+ - sft
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+ - transformers
11
+ - trl
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+ - unsloth
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+ ---
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+
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+ # Model Card for Model ID
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+
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+ <!-- Provide a quick summary of what the model is/does. -->
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+
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+
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+
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+ ## Model Details
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+
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+ ### Model Description
24
+
25
+ <!-- Provide a longer summary of what this model is. -->
26
+
27
+
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+
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+ - **Developed by:** [More Information Needed]
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+ - **Funded by [optional]:** [More Information Needed]
31
+ - **Shared by [optional]:** [More Information Needed]
32
+ - **Model type:** [More Information Needed]
33
+ - **Language(s) (NLP):** [More Information Needed]
34
+ - **License:** [More Information Needed]
35
+ - **Finetuned from model [optional]:** [More Information Needed]
36
+
37
+ ### Model Sources [optional]
38
+
39
+ <!-- Provide the basic links for the model. -->
40
+
41
+ - **Repository:** [More Information Needed]
42
+ - **Paper [optional]:** [More Information Needed]
43
+ - **Demo [optional]:** [More Information Needed]
44
+
45
+ ## Uses
46
+
47
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
48
+
49
+ ### Direct Use
50
+
51
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
52
+
53
+ [More Information Needed]
54
+
55
+ ### Downstream Use [optional]
56
+
57
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
58
+
59
+ [More Information Needed]
60
+
61
+ ### Out-of-Scope Use
62
+
63
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
64
+
65
+ [More Information Needed]
66
+
67
+ ## Bias, Risks, and Limitations
68
+
69
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
70
+
71
+ [More Information Needed]
72
+
73
+ ### Recommendations
74
+
75
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
76
+
77
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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+
79
+ ## How to Get Started with the Model
80
+
81
+ Use the code below to get started with the model.
82
+
83
+ [More Information Needed]
84
+
85
+ ## Training Details
86
+
87
+ ### Training Data
88
+
89
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
90
+
91
+ [More Information Needed]
92
+
93
+ ### Training Procedure
94
+
95
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
96
+
97
+ #### Preprocessing [optional]
98
+
99
+ [More Information Needed]
100
+
101
+
102
+ #### Training Hyperparameters
103
+
104
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
105
+
106
+ #### Speeds, Sizes, Times [optional]
107
+
108
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
109
+
110
+ [More Information Needed]
111
+
112
+ ## Evaluation
113
+
114
+ <!-- This section describes the evaluation protocols and provides the results. -->
115
+
116
+ ### Testing Data, Factors & Metrics
117
+
118
+ #### Testing Data
119
+
120
+ <!-- This should link to a Dataset Card if possible. -->
121
+
122
+ [More Information Needed]
123
+
124
+ #### Factors
125
+
126
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
127
+
128
+ [More Information Needed]
129
+
130
+ #### Metrics
131
+
132
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
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+
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+ [More Information Needed]
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+
136
+ ### Results
137
+
138
+ [More Information Needed]
139
+
140
+ #### Summary
141
+
142
+
143
+
144
+ ## Model Examination [optional]
145
+
146
+ <!-- Relevant interpretability work for the model goes here -->
147
+
148
+ [More Information Needed]
149
+
150
+ ## Environmental Impact
151
+
152
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
153
+
154
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
155
+
156
+ - **Hardware Type:** [More Information Needed]
157
+ - **Hours used:** [More Information Needed]
158
+ - **Cloud Provider:** [More Information Needed]
159
+ - **Compute Region:** [More Information Needed]
160
+ - **Carbon Emitted:** [More Information Needed]
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+
162
+ ## Technical Specifications [optional]
163
+
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+ ### Model Architecture and Objective
165
+
166
+ [More Information Needed]
167
+
168
+ ### Compute Infrastructure
169
+
170
+ [More Information Needed]
171
+
172
+ #### Hardware
173
+
174
+ [More Information Needed]
175
+
176
+ #### Software
177
+
178
+ [More Information Needed]
179
+
180
+ ## Citation [optional]
181
+
182
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
183
+
184
+ **BibTeX:**
185
+
186
+ [More Information Needed]
187
+
188
+ **APA:**
189
+
190
+ [More Information Needed]
191
+
192
+ ## Glossary [optional]
193
+
194
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
195
+
196
+ [More Information Needed]
197
+
198
+ ## More Information [optional]
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+
200
+ [More Information Needed]
201
+
202
+ ## Model Card Authors [optional]
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+
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+ [More Information Needed]
205
+
206
+ ## Model Card Contact
207
+
208
+ [More Information Needed]
209
+ ### Framework versions
210
+
211
+ - PEFT 0.21.2
lora/adapter_config.json ADDED
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+ {{- "\n" }}
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+ {{- tool | tojson }}
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+ {%- endfor %}
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+ "chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0]['role'] == 'system' %}\n {{- messages[0]['content'] }}\n {%- else %}\n {{- 'You are Qwen, created by Alibaba Cloud. 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 Qwen, created by Alibaba Cloud. You 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"
218
+ }