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  1. .gitattributes +1 -0
  2. README.md +54 -127
  3. special_tokens_map.json +31 -0
  4. tokenizer.json +3 -0
  5. tokenizer_config.json +239 -0
.gitattributes CHANGED
@@ -33,3 +33,4 @@ 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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  *tfevents* 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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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ tokenizer.json filter=lfs diff=lfs merge=lfs -text
README.md CHANGED
@@ -1,127 +1,54 @@
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-
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- ```markdown
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- ---
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- base_model:
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- - openfree/Darwin-Qwen3-4B
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- - Lucidity-AI/Astral-4B-Coder
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- library_name: transformers
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- tags:
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- - merge
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- - mergekit
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- - qwen
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- - qwen2.5
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- - safetensors
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- - code
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- - logic
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- license: apache-2.0
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- language:
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- - en
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- ---
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-
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- # Darwin-Astral-4B-Coder
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-
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- !
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-
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- **Darwin-Astral-4B-Coder** is a specialized 4B parameter model resulting from the amalgamation of high-performance logic and coding models. It was created to combine the evolutionary reasoning capabilities of the *Darwin* series with the precise code generation of the *Astral* series, resulting in a lightweight but powerful coding assistant.
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-
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- This model was merged using the custom **Amalgamation AI** engine (powered by `mergekit`).
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-
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- ## 👊 The "Within Us" Philosophy
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- This model represents a fusion of two distinct intelligences:
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- 1. **Logic & Reasoning:** Inherited from `openfree/Darwin-Qwen3-4B`.
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- 2. **Coding Proficiency:** Inherited from `Lucidity-AI/Astral-4B-Coder`.
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-
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- By merging these, we aim to create a "Thinking Coder" capable of understanding complex prompts and generating efficient, clean code on consumer hardware.
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-
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- ## 💻 Technical Details
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-
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- * **Base Architecture:** Qwen2.5 (4B)
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- * **Merge Method:** SLERP (Spherical Linear Interpolation)
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- * **Precision:** Float16
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- * **Layer Count:** 36 Layers
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- * **Developer:** Guy DuGan II (Within Us AI)
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-
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- ### Merge Configuration
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-
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- The following configuration was used to generate this model:
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-
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- ```yaml
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- models:
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- - model: openfree/Darwin-Qwen3-4B
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- # No parameters necessary for base model
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- - model: Lucidity-AI/Astral-4B-Coder
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- parameters:
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- density: 0.5
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- weight: 0.5
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- merge_method: slerp
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- base_model: openfree/Darwin-Qwen3-4B
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- parameters:
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- t:
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- - filter: embed_tokens
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- value: 0.0
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- - filter: self_attn
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- value: 0.5
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- - filter: mlp
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- value: 0.5
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- - filter: lm_head
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- value: 1.0
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- - value: 0.5 # Catch-all for norm layers
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- dtype: float16
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-
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- ```
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-
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- ## 🚀 How to Use (Transformers)
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-
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- You can run this model directly using the Hugging Face `transformers` library.
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-
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- ```python
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- import torch
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- from transformers import AutoTokenizer, AutoModelForCausalLM
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-
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- model_id = "WithinUsAI/Darwin-Astral-4B-Coder" # Replace with your actual username/repo
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-
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- tokenizer = AutoTokenizer.from_pretrained(model_id)
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- model = AutoModelForCausalLM.from_pretrained(
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- model_id,
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- torch_dtype=torch.float16,
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- device_map="auto"
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- )
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-
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- prompt = "Write a Python script to merge two sorted lists."
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- messages = [
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- {"role": "system", "content": "You are an advanced coding assistant."},
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- {"role": "user", "content": prompt}
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- ]
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-
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- text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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- inputs = tokenizer(text, return_tensors="pt").to(model.device)
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-
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- outputs = model.generate(
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- **inputs,
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- max_new_tokens=512,
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- do_sample=True,
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- temperature=0.7
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- )
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-
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- print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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-
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- ```
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-
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- ## 📜 License
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-
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- This model is released under the **Apache 2.0** license, following the licensing of the base Qwen models. Please refer to the original model cards for specific restrictions.
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-
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- ---
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-
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- *Created with Amalgamation AI by Within Us AI.*
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-
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- ```
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-
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- ---
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-
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- ### **Next Step: GGUF Conversion**
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- Once you have uploaded this to Hugging Face (or even if you keep it local), the next logical step is to make it runnable on your iPhone, older laptops, or via Ollama.
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-
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- **Ready for the GGUF script?** I can provide a `convert_to_gguf.py` script that handles the quantization (making it smaller/faster) automatically.
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-
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- ```
 
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+ ---
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+ base_model: []
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+ library_name: transformers
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+ tags:
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+ - mergekit
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+ - merge
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+
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+ ---
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+ # WithinUs_CPU_Hybrid
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+
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+ This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
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+
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+ ## Merge Details
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+ ### Merge Method
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+
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+ This model was merged using the [SLERP](https://en.wikipedia.org/wiki/Slerp) merge method.
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+
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+ ### Models Merged
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+
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+ The following models were included in the merge:
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+ * X:/Genesis_X/models/openfree-Darwin-Qwen3-4B
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+ * X:/Genesis_X/models/Lucidity-AI-Astral-4B-Coder
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+
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+ ### Configuration
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+
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+ The following YAML configuration was used to produce this model:
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+
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+ ```yaml
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+ base_model: X:/Genesis_X/models/Lucidity-AI-Astral-4B-Coder
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+ dtype: float16
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+ merge_method: slerp
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+ parameters:
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+ t:
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+ - filter: mlp
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+ value: 0.5
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+ - filter: lm_head
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+ value: 1.0
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+ - value: 0.5
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+ slices:
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+ - sources:
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+ - layer_range:
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+ - 0
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+ - 36
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+ model: X:/Genesis_X/models/Lucidity-AI-Astral-4B-Coder
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+ - layer_range:
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+ - 0
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+ - 36
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+ model: X:/Genesis_X/models/openfree-Darwin-Qwen3-4B
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+
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+ ```
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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