commit 8f052babb81e16b9eca73c3c45e98318cd80d65e
Author: ModelHub XC <noreply@modelhub.org.cn>
Date:   Mon Apr 13 05:40:56 2026 +0800

    初始化项目，由ModelHub XC社区提供模型
    
    Model: zkaedi/gemma-7b-solidity-energy-signatures
    Source: Original Platform

diff --git a/.gitattributes b/.gitattributes
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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
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+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text
+gemma-7b.Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text
+gemma-2-9b-it.Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
+gemma-2-9b-it.Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+checkpoint-54/tokenizer.json filter=lfs diff=lfs merge=lfs -text
+checkpoint-81/tokenizer.json filter=lfs diff=lfs merge=lfs -text
diff --git a/Modelfile b/Modelfile
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index 0000000..4b29c06
--- /dev/null
+++ b/Modelfile
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+
+FROM gemma-2-9b-it.Q8_0.gguf
+TEMPLATE """<start_of_turn>user
+{{ if .System }}{{ .System }} {{ end }}{{ .Prompt }}<end_of_turn>
+<start_of_turn>model
+{{ .Response }}<end_of_turn>
+"""
+PARAMETER repeat_penalty 1
+PARAMETER stop "<start_of_turn>"
+PARAMETER stop "<end_of_turn>"
+PARAMETER penalize_newline false
+PARAMETER temperature 1.5
+PARAMETER min_p 0.1
+PARAMETER num_ctx 4096
\ No newline at end of file
diff --git a/README.md b/README.md
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--- /dev/null
+++ b/README.md
@@ -0,0 +1,63 @@
+---
+base_model: google/gemma-2-9b
+library_name: peft
+model_name: retrained_adapter_v4
+tags:
+- base_model:adapter:google/gemma-2-9b
+- lora
+- sft
+- transformers
+- trl
+- unsloth
+licence: license
+pipeline_tag: text-generation
+---
+
+# Model Card for retrained_adapter_v4
+
+This model is a fine-tuned version of [google/gemma-2-9b](https://huggingface.co/google/gemma-2-9b).
+It has been trained using [TRL](https://github.com/huggingface/trl).
+
+## Quick start
+
+```python
+from transformers import pipeline
+
+question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
+generator = pipeline("text-generation", model="None", device="cuda")
+output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
+print(output["generated_text"])
+```
+
+## Training procedure
+
+ 
+
+
+
+This model was trained with SFT.
+
+### Framework versions
+
+- PEFT 0.18.1
+- TRL: 0.29.0
+- Transformers: 5.0.0
+- Pytorch: 2.10.0+cu128
+- Datasets: 4.0.0
+- Tokenizers: 0.22.2
+
+## Citations
+
+
+
+Cite TRL as:
+    
+```bibtex
+@software{vonwerra2020trl,
+  title   = {{TRL: Transformers Reinforcement Learning}},
+  author  = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin},
+  license = {Apache-2.0},
+  url     = {https://github.com/huggingface/trl},
+  year    = {2020}
+}
+```
\ No newline at end of file
diff --git a/adapter_config.json b/adapter_config.json
new file mode 100644
index 0000000..b167a47
--- /dev/null
+++ b/adapter_config.json
@@ -0,0 +1,50 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": {
+    "base_model_class": "Gemma2ForCausalLM",
+    "parent_library": "transformers.models.gemma2.modeling_gemma2",
+    "unsloth_fixed": true
+  },
+  "base_model_name_or_path": "unsloth/gemma-2-9b-it-bnb-4bit",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 128,
+  "lora_bias": false,
+  "lora_dropout": 0,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.18.1",
+  "qalora_group_size": 16,
+  "r": 64,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "down_proj",
+    "q_proj",
+    "v_proj",
+    "k_proj",
+    "up_proj",
+    "gate_proj",
+    "o_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/adapter_model.safetensors b/adapter_model.safetensors
new file mode 100644
index 0000000..36a69d6
--- /dev/null
+++ b/adapter_model.safetensors
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+oid sha256:e7de9f78ba95e1c30aadda38b36034995efbcfef1531ef1e3a6e725c1dd5100e
+size 864368280
diff --git a/benchmark_results.md b/benchmark_results.md
new file mode 100644
index 0000000..b1f0918
--- /dev/null
+++ b/benchmark_results.md
@@ -0,0 +1,3 @@
+
+# 🔱 ZKAEDI PRIME Benchmark
+...paste full benchmark content here...
diff --git a/chat_template.jinja b/chat_template.jinja
new file mode 100644
index 0000000..923ec25
--- /dev/null
+++ b/chat_template.jinja
@@ -0,0 +1,4 @@
+{{ bos_token }}{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not supported') }}{% endif %}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if (message['role'] == 'assistant') %}{% set role = 'model' %}{% else %}{% set role = message['role'] %}{% endif %}{{ '<start_of_turn>' + role + '
+' + message['content'] | trim + '<end_of_turn>
+' }}{% endfor %}{% if add_generation_prompt %}{{'<start_of_turn>model
+'}}{% endif %}
\ No newline at end of file
diff --git a/checkpoint-54/README.md b/checkpoint-54/README.md
new file mode 100644
index 0000000..9716635
--- /dev/null
+++ b/checkpoint-54/README.md
@@ -0,0 +1,209 @@
+---
+base_model: google/gemma-2-9b
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:google/gemma-2-9b
+- lora
+- sft
+- transformers
+- trl
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- 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. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+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).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.18.1
\ No newline at end of file
diff --git a/checkpoint-54/adapter_config.json b/checkpoint-54/adapter_config.json
new file mode 100644
index 0000000..ff42dd5
--- /dev/null
+++ b/checkpoint-54/adapter_config.json
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+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": {
+    "base_model_class": "Gemma2ForCausalLM",
+    "parent_library": "transformers.models.gemma2.modeling_gemma2",
+    "unsloth_fixed": true
+  },
+  "base_model_name_or_path": "unsloth/gemma-2-9b-it-bnb-4bit",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
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+  "megatron_core": "megatron.core",
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+    "o_proj",
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+    "q_proj",
+    "up_proj"
+  ],
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+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/checkpoint-54/adapter_model.safetensors b/checkpoint-54/adapter_model.safetensors
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+{
+  "backend": "tokenizers",
+  "bos_token": "<bos>",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<eos>",
+  "extra_special_tokens": [
+    "<start_of_turn>",
+    "<end_of_turn>"
+  ],
+  "is_local": false,
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+  "model_max_length": 1000000000000000019884624838656,
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+  "tokenizer_class": "GemmaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false
+}
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+}
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diff --git a/checkpoint-81/README.md b/checkpoint-81/README.md
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--- /dev/null
+++ b/checkpoint-81/README.md
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+---
+base_model: google/gemma-2-9b
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:google/gemma-2-9b
+- lora
+- sft
+- transformers
+- trl
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- 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. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+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).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.18.1
\ No newline at end of file
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\ No newline at end of file
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+    "model.layers.9.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
+    "model.layers.9.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
+    "model.layers.9.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
+    "model.layers.9.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
+    "model.layers.9.post_feedforward_layernorm.weight": "model-00002-of-00004.safetensors",
+    "model.layers.9.pre_feedforward_layernorm.weight": "model-00002-of-00004.safetensors",
+    "model.layers.9.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
+    "model.layers.9.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
+    "model.layers.9.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
+    "model.layers.9.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
+    "model.norm.weight": "model-00004-of-00004.safetensors"
+  }
+}
diff --git a/special_tokens_map.json b/special_tokens_map.json
new file mode 100644
index 0000000..8d6368f
--- /dev/null
+++ b/special_tokens_map.json
@@ -0,0 +1,34 @@
+{
+  "additional_special_tokens": [
+    "<start_of_turn>",
+    "<end_of_turn>"
+  ],
+  "bos_token": {
+    "content": "<bos>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "<eos>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<pad>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}
diff --git a/tokenizer.json b/tokenizer.json
new file mode 100644
index 0000000..6523cc0
--- /dev/null
+++ b/tokenizer.json
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:394ace002a144ac6ad5486387502f2d36f70c087310c3d907857240c76fcb36e
+size 34362748
diff --git a/tokenizer.model b/tokenizer.model
new file mode 100644
index 0000000..796efe9
--- /dev/null
+++ b/tokenizer.model
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:61a7b147390c64585d6c3543dd6fc636906c9af3865a5548f27f31aee1d4c8e2
+size 4241003
diff --git a/tokenizer_config.json b/tokenizer_config.json
new file mode 100644
index 0000000..59c5bb0
--- /dev/null
+++ b/tokenizer_config.json
@@ -0,0 +1,19 @@
+{
+  "backend": "tokenizers",
+  "bos_token": "<bos>",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<eos>",
+  "extra_special_tokens": [],
+  "from_slow": true,
+  "is_local": false,
+  "legacy": false,
+  "mask_token": "<mask>",
+  "model_max_length": 8192,
+  "pad_token": "<pad>",
+  "padding_side": "left",
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "GemmaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false
+}
diff --git a/viz_waterfall.html b/viz_waterfall.html
new file mode 100644
index 0000000..789d3bc
--- /dev/null
+++ b/viz_waterfall.html
@@ -0,0 +1,228 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+<meta charset="UTF-8">
+<meta name="viewport" content="width=device-width,initial-scale=1">
+<title>ZKAEDI PRIME — Hamiltonian Self-Similarity Waterfall</title>
+<link href="https://fonts.googleapis.com/css2?family=JetBrains+Mono:wght@400;700&family=Orbitron:wght@700;900&display=swap" rel="stylesheet">
+<style>
+*{box-sizing:border-box;margin:0;padding:0}
+body{background:#000;color:#C8BFAE;font-family:'JetBrains Mono',monospace;font-size:11px;display:flex;flex-direction:column;align-items:center;justify-content:center;height:100vh;overflow:hidden;padding:8px}
+h1{font-family:'Orbitron',monospace;font-size:10px;letter-spacing:4px;color:#CC0030;margin-bottom:3px;text-align:center}
+.sub{font-size:8px;color:#3A3D55;letter-spacing:2px;margin-bottom:8px;text-align:center}
+#c{display:block;border:1px solid #1C1E30}
+.metrics{display:flex;gap:16px;margin-top:8px;font-size:8px;color:#3A3D55;letter-spacing:1px;flex-wrap:wrap;justify-content:center}
+.mv{color:#00BBCC}
+</style>
+</head>
+<body>
+<h1>HAMILTONIAN SELF-SIMILARITY WATERFALL</h1>
+<div class="sub">H_t DECOMPOSED ACROSS SCALES τ=1,2,4,8,16,32 — SELF-SIMILAR STRUCTURE REVEALED</div>
+<canvas id="c"></canvas>
+<div class="metrics">
+  FRACTAL DIM: <span class="mv" id="fd">—</span>&nbsp;&nbsp;
+  SCALE CORR: <span class="mv" id="sc">—</span>&nbsp;&nbsp;
+  HURST (field): <span class="mv" id="hf">—</span>&nbsp;&nbsp;
+  DOMINANT SCALE: <span class="mv" id="ds">—</span>
+</div>
+
+<script>
+const C=document.getElementById('c');
+const ctx=C.getContext('2d');
+const W=Math.min(window.innerWidth-40,680);
+const H=Math.min(window.innerHeight-110,420);
+C.width=W;C.height=H;
+
+// ZKAEDI PRIME — generate H_t field
+const sigmoid=x=>1/(1+Math.exp(-Math.max(-20,Math.min(20,x))));
+function genHfield(N,eta=0.42,gamma=0.35,beta=0.10,sigma=0.05){
+  let seed=7777;
+  const rng=()=>{seed=(seed*1664525+1013904223)&0xffffffff;return((seed>>>0)/0xffffffff-.5)*2;};
+  const H=new Float64Array(N);
+  const H0=0.5;
+  H[0]=H0;
+  for(let t=1;t<N;t++){
+    const sg=sigmoid(gamma*H[t-1]);
+    H[t]=H0+eta*H[t-1]*sg+sigma*rng()*(1+beta*Math.abs(H[t-1]));
+  }
+  return H;
+}
+
+// Smooth at scale s (box average)
+function smoothAt(H,scale){
+  const N=H.length;
+  const out=new Float64Array(N);
+  for(let i=0;i<N;i++){
+    let sum=0,cnt=0;
+    for(let k=Math.max(0,i-scale);k<=Math.min(N-1,i+scale);k++){sum+=H[k];cnt++;}
+    out[i]=sum/cnt;
+  }
+  return out;
+}
+
+// Scale-to-scale correlation
+function corr(a,b){
+  const n=Math.min(a.length,b.length);
+  let ma=0,mb=0;
+  for(let i=0;i<n;i++){ma+=a[i];mb+=b[i];}
+  ma/=n;mb/=n;
+  let num=0,da=0,db=0;
+  for(let i=0;i<n;i++){num+=(a[i]-ma)*(b[i]-mb);da+=(a[i]-ma)**2;db+=(b[i]-mb)**2;}
+  return (da>0&&db>0)?num/Math.sqrt(da*db):0;
+}
+
+const N=600;
+const H=genHfield(N);
+const SCALES=[1,2,4,8,16,32];
+const COLORS=[
+  'rgba(0,187,204,0.8)',    // τ=1  cyan
+  'rgba(0,204,122,0.8)',    // τ=2  jade
+  'rgba(201,168,76,0.8)',   // τ=4  gold
+  'rgba(204,85,0,0.8)',     // τ=8  amber
+  'rgba(148,0,204,0.8)',    // τ=16 orchid
+  'rgba(204,0,48,0.8)',     // τ=32 crimson
+];
+const LABELS=['τ=1','τ=2','τ=4','τ=8','τ=16','τ=32'];
+
+const scales=SCALES.map(s=>smoothAt(H,s));
+const LAY_H=(H-20)/SCALES.length; // height per scale row
+const PAD_L=52, PAD_R=14, PAD_T=12, PAD_B=20;
+
+// For each scale, find min/max for scaling
+const stats=scales.map(s=>{
+  let mn=Infinity,mx=-Infinity;
+  for(const v of s){if(v<mn)mn=v;if(v>mx)mx=v;}
+  return{mn,mx};
+});
+
+// Scale correlations
+const corrs=[];
+for(let i=0;i<scales.length-1;i++) corrs.push(corr(scales[i],scales[i+1]));
+const avgCorr=corrs.reduce((a,b)=>a+b,0)/corrs.length;
+
+// Hurst of H field
+function simpleHurst(arr){
+  const n=arr.length;
+  const m=arr.reduce((a,b)=>a+b,0)/n;
+  let cum=0,mx=-Infinity,mn=Infinity;
+  for(const v of arr){cum+=v-m;if(cum>mx)mx=cum;if(cum<mn)mn=cum;}
+  const R=mx-mn;
+  const S=Math.sqrt(arr.reduce((a,v)=>a+(v-m)**2,0)/n);
+  return S>0?Math.log(R/S)/Math.log(n):0.5;
+}
+const hfHurst=simpleHurst(Array.from(H));
+
+// Draw background
+ctx.fillStyle='#000';ctx.fillRect(0,0,W,H);
+
+// Grid lines
+ctx.strokeStyle='rgba(200,191,174,0.04)';ctx.lineWidth=0.5;
+for(let t=0;t<N;t+=60){
+  const x=PAD_L+(t/N)*(W-PAD_L-PAD_R);
+  ctx.beginPath();ctx.moveTo(x,PAD_T);ctx.lineTo(x,H-PAD_B);ctx.stroke();
+}
+
+// Draw each scale as filled band + line, waterfall stacked
+for(let si=0;si<scales.length;si++){
+  const s=scales[si];
+  const {mn,mx}=stats[si];
+  const range=mx-mn||1;
+  const yBase=PAD_T+si*LAY_H+LAY_H;      // bottom of this row
+  const yTop=PAD_T+si*LAY_H;              // top of this row
+  const rowH=LAY_H-1;
+  const color=COLORS[si];
+  const scale=SCALES[si];
+
+  // Fill band
+  ctx.beginPath();
+  for(let t=0;t<N;t++){
+    const x=PAD_L+(t/N)*(W-PAD_L-PAD_R);
+    const yn=yTop+rowH*(1-(s[t]-mn)/range);
+    t===0?ctx.moveTo(x,yn):ctx.lineTo(x,yn);
+  }
+  ctx.lineTo(PAD_L+(N-1)/N*(W-PAD_L-PAD_R),yBase);
+  ctx.lineTo(PAD_L,yBase);
+  ctx.closePath();
+  const grad=ctx.createLinearGradient(0,yTop,0,yBase);
+  grad.addColorStop(0,color.replace('0.8','0.18'));
+  grad.addColorStop(1,'rgba(0,0,0,0)');
+  ctx.fillStyle=grad;ctx.fill();
+
+  // Line
+  ctx.beginPath();
+  for(let t=0;t<N;t++){
+    const x=PAD_L+(t/N)*(W-PAD_L-PAD_R);
+    const yn=yTop+rowH*(1-(s[t]-mn)/range);
+    t===0?ctx.moveTo(x,yn):ctx.lineTo(x,yn);
+  }
+  ctx.strokeStyle=color;ctx.lineWidth=si===0?1.2:1.0;ctx.stroke();
+
+  // Row separator
+  ctx.strokeStyle='rgba(200,191,174,0.06)';ctx.lineWidth=0.5;
+  ctx.beginPath();ctx.moveTo(PAD_L,yBase);ctx.lineTo(W-PAD_R,yBase);ctx.stroke();
+
+  // Label
+  ctx.fillStyle=color;ctx.font="bold 8px 'Orbitron'";
+  ctx.fillText(LABELS[si],4,yTop+rowH*0.55);
+  // Corr with next scale
+  if(si<corrs.length){
+    ctx.fillStyle='rgba(200,191,174,0.3)';ctx.font="7px 'JetBrains Mono'";
+    ctx.fillText('r='+corrs[si].toFixed(2),4,yTop+rowH*0.85);
+  }
+
+  // Self-similarity markers: where scale-1 and scale-s are most correlated — highlight peaks
+  if(si===0){
+    // Mark phase transitions: points where dH/dt spikes
+    const dH=[];
+    for(let t=1;t<N;t++) dH.push(Math.abs(s[t]-s[t-1]));
+    const dMean=dH.reduce((a,b)=>a+b,0)/dH.length;
+    const dStd=Math.sqrt(dH.reduce((a,v)=>a+(v-dMean)**2,0)/dH.length);
+    for(let t=1;t<N;t++){
+      if(dH[t-1]>dMean+2.2*dStd){
+        const x=PAD_L+(t/N)*(W-PAD_L-PAD_R);
+        ctx.strokeStyle='rgba(204,0,48,0.5)';ctx.lineWidth=1;ctx.setLineDash([1,2]);
+        ctx.beginPath();ctx.moveTo(x,PAD_T);ctx.lineTo(x,H-PAD_B);ctx.stroke();ctx.setLineDash([]);
+      }
+    }
+  }
+}
+
+// Time axis
+ctx.fillStyle='rgba(200,191,174,0.25)';ctx.font="7px 'JetBrains Mono'";
+for(let t=0;t<N;t+=100){
+  const x=PAD_L+(t/N)*(W-PAD_L-PAD_R);
+  ctx.fillText('t='+t,x-8,H-4);
+}
+ctx.fillText('t →',W-30,H-4);
+
+// Spectral power analysis (RMS at each scale)
+const powers=scales.map((s,i)=>{
+  const mn=stats[i].mn;
+  return Math.sqrt(s.reduce((a,v)=>a+(v-mn)**2,0)/N);
+});
+const maxP=Math.max(...powers);
+
+// Mini power spectrum bar in top-right
+const sbX=W-80,sbY=PAD_T,sbW=60,sbH=40;
+ctx.strokeStyle='rgba(200,191,174,0.1)';ctx.lineWidth=0.5;
+ctx.strokeRect(sbX,sbY,sbW,sbH);
+ctx.fillStyle='rgba(200,191,174,0.15)';ctx.font="6px 'JetBrains Mono'";
+ctx.fillText('POWER',sbX+16,sbY-2);
+for(let si=0;si<SCALES.length;si++){
+  const bx=sbX+si*(sbW/SCALES.length)+1;
+  const bh=(powers[si]/maxP)*sbH*0.9;
+  ctx.fillStyle=COLORS[si].replace('0.8','0.7');
+  ctx.fillRect(bx,sbY+sbH-bh,sbW/SCALES.length-2,bh);
+}
+
+// Fractal dimension estimate: D = 2 - H
+const D=(2-hfHurst).toFixed(3);
+document.getElementById('fd').textContent=D;
+document.getElementById('sc').textContent=avgCorr.toFixed(3);
+document.getElementById('hf').textContent=hfHurst.toFixed(3);
+// Dominant scale: highest power
+const domIdx=powers.indexOf(Math.max(...powers));
+document.getElementById('ds').textContent=LABELS[domIdx];
+</script>
+</body>
+</html>
diff --git a/zkaedi_audit.py b/zkaedi_audit.py
new file mode 100644
index 0000000..b853f3b
--- /dev/null
+++ b/zkaedi_audit.py
@@ -0,0 +1,31 @@
+import requests, json, time, re
+
+# ── Config ───────────────────────────────────────────────────────────────────
+ETHERSCAN_KEY = "YOUR_ETHERSCAN_API_KEY"
+
+# ── Vuln type alias map ──────────────────────────────────────────────────────
+VULN_TYPE_ALIASES = {
+    "flash_loan_oracle":      ["flash_loan_oracle", "price manipulation", "oracle manipulation", "flash loan oracle"],
+    "flash_loan_governance":  ["flash_loan_governance", "flash loan governance", "governance attack"],
+    "reentrancy":             ["reentrancy", "re-entrancy", "recursive call"],
+    "price_manipulation":     ["price_manipulation", "price manipulation", "oracle manipulation"],
+    "improper_initialization":["improper_initialization", "improper initialization", "zero hash", "uninitialized", "merkle root"],
+    "uninitialized_proxy":    ["uninitialized_proxy", "uninitialized proxy", "uninitialized wallet", "selfdestruct", "self-destruct", "kill"],
+    "donation_attack":        ["donation_attack", "donation attack", "violates", "health check", "edonation", "bad debt"],
+    "read_only_reentrancy":   ["read_only_reentrancy", "read-only reentrancy", "read only reentrancy", "view reentrancy"],
+    "access_control":         ["access_control", "access control", "unauthorized", "missing modifier", "privilege escalation", "permit", "permit signature", "signature re-use", "signature reuse"],
+}
+
+TARGETS = {
+    "DAO (Reentrancy - $60M 2016)":                          {"address": "0xBB9bc244D798123fDe783fCc1C72d3Bb8C189413", "expected_type": "reentrancy",             "expected_severity": "CRITICAL", "expected_lyapunov_min": 0.8},
+    "Beanstalk (Governance Flash Loan - $182M 2022)":        {"address": "0xC1E088fC1323b20BCBee9bd1B9fC9546db5624C5", "expected_type": "flash_loan_governance",   "expected_severity": "CRITICAL", "expected_lyapunov_min": 0.7},
+    "Harvest USDC Vault (Oracle Manipulation - $34M 2020)":  {"address": "0x3461B89F2c334aE37e0C3c1bD4d9c027d939fBc9", "expected_type": "flash_loan_oracle",       "expected_severity": "CRITICAL", "expected_lyapunov_min": 0.6},
+    "Compound cETH (Flash Loan Attack Surface - $150M 2021)":{"address": "0x4Ddc2D193948926D02f9B1fE9e1daa0718270ED5", "expected_type": "price_manipulation",      "expected_severity": "CRITICAL", "expected_lyapunov_min": 0.6},
+    "Uniswap V1 imBTC Pool (Reentrancy ERC777 - $300K 2020)":{"address": "0x2a1530C4C41db0B0b2bB646CB5Eb1A67b7158667", "expected_type": "reentrancy",             "expected_severity": "CRITICAL", "expected_lyapunov_min": 0.5},
+    "Nomad Bridge (Improper Initialization - $190M 2022)":   {"address": "0x88A69B4E698A4B090DF6CF5Bd7B2D47325Ad30A3", "expected_type": "improper_initialization", "expected_severity": "CRITICAL", "expected_lyapunov_min": 0.7},
+    "Parity Multisig (Uninitialized Proxy - $150M 2017)":    {"address": "0x863DF6BFa4469f3ead0bE8f9F2AAE51c91A907b4", "expected_type": "uninitialized_proxy",     "expected_severity": "CRITICAL", "expected_lyapunov_min": 0.7},
+    "Euler Finance (Donation Attack - $197M 2023)":          {"address": "0x27182842E098f60e3D576794A5bFFb0777E025d3", "expected_type": "donation_attack",         "expected_severity": "CRITICAL", "expected_lyapunov_min": 0.8},
+    "Cream Finance (Read-Only Reentrancy - $130M 2021)":     {"address": "0x797AAB1ce7c01eB727ab980762bA88e7133d2157", "expected_type": "read_only_reentrancy",     "expected_severity": "HIGH",     "expected_lyapunov_min": 0.5},
+    "Multichain (Access Control - $126M 2023)":              {"address": "0xC10Ef9F491C9B59f936957026020C321651ac078", "expected_type": "access_control",          "expected_severity": "CRITICAL", "expected_lyapunov_min": 0.6},
+}
+# Full LOCAL_SOURCE and audit logic: see zkaedi_audit.py in this repo