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  ---
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- license: apache-2.0
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- language: en
 
 
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  tags:
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- - mergekit
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- - slerp
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- - minicpm
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- - zoder
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- - gguf
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- - ollama
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- created_by: Komandan Nasa
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- ---
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-
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- # 🤖 Zoder 1.0-1B
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- Custom SLERP-merged AI assistant by **Komandan Nasa** (Bakso Bangi Pak Romdani, Kediri, Indonesia).
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-
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- ## Features
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- - Chat Template & System Prompt configured
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- - ✅ GGUF Q4_K_M quantized version (~700MB)
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- - ✅ Gradio Web UI included
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- - ✅ Ollama compatible with Modelfile
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- - ✅ Optimized for Termux deployment
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- - ✅ 100% benchmark pass rate (8/8 tests)
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  ## Merge Details
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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- | Parameter | Value |
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- |-----------|-------|
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- | Base Model A | openbmb/MiniCPM5-1B |
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- | Base Model B | GnLOLot/MiniCPM5-1B-Claude-Opus-Fable5-V2-Thinking |
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- | Method | SLERP |
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- | T-value (self_attn) | [0, 0.5, 0.3, 0.7, 1] |
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- | T-value (mlp) | [1, 0.5, 0.7, 0.3, 0] |
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- | T-value (default) | 0.5 |
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- | Dtype | float16 |
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- | Layers | 24 |
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-
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- ## Files
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-
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- | File | Size | Description |
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- |------|------|-------------|
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- | `model.safetensors` | ~2GB | Full float16 model |
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- | `Zoder1.0-1B-Q4_K_M.gguf` | ~700MB | Quantized for mobile/Termux/Ollama |
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- | `zoder_gradio.py` | ~3KB | Web UI script |
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- | `Modelfile` | ~1KB | Ollama configuration |
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- | `install_zoder_ollama.sh` | ~2KB | Termux installer script |
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-
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- ## Quick Start with Ollama
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-
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- ```bash
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- # Pull from HuggingFace (after creating model locally)
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- ollama create zoder -f Modelfile
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-
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- # Or pull directly (if published to Ollama library)
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- ollama run zoder
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- ```
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-
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- ## Usage
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-
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- ### Transformers (Full Model)
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-
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- ```python
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- from transformers import AutoTokenizer, AutoModelForCausalLM
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-
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- tokenizer = AutoTokenizer.from_pretrained("Nasaawakening/Zoder1.0-1B", trust_remote_code=True)
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- model = AutoModelForCausalLM.from_pretrained("Nasaawakening/Zoder1.0-1B", trust_remote_code=True, torch_dtype="float16", device_map="auto")
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-
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- messages = [
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- {"role": "system", "content": "You are Zoder, a helpful AI assistant."},
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- {"role": "user", "content": "Hello!"}
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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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- outputs = model.generate(**inputs, max_new_tokens=256)
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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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- ### GGUF (llama.cpp / Termux)
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-
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- ```bash
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- huggingface-cli download Nasaawakening/Zoder1.0-1B Zoder1.0-1B-Q4_K_M.gguf --local-dir ~/zoder
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- llama-server -m ~/zoder/Zoder1.0-1B-Q4_K_M.gguf --port 8080
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  ```
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-
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- ### Gradio Web UI
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-
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- ```bash
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- pip install gradio transformers torch
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- python zoder_gradio.py
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- ```
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-
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- ### Termux Ollama Deployment
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-
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- ```bash
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- # Download and run installer
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- bash install_zoder_ollama.sh
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-
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- # Run Zoder
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- proot-distro login ubuntu -- ollama run zoder
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- ```
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-
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- ## Benchmark Results
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-
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- | Test | Status |
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- |------|--------|
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- | Basic Conversation | ✅ PASS |
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- | Logical Reasoning | ✅ PASS |
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- | Code Generation (Python) | ✅ PASS |
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- | Creative Writing | ✅ PASS |
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- | Instruction Following | ✅ PASS |
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- | Multi-turn Memory | ✅ PASS |
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- | Math Problem | ✅ PASS |
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- | Termux Knowledge | ✅ PASS |
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- | **Pass Rate** | **100% (8/8)** |
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-
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- ## Built With ❤️ in Kediri, Indonesia
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-
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- Created by Komandan Nasa from Bakso Bangi Pak Romdani.
 
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  ---
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+ base_model:
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+ - openbmb/MiniCPM5-1B
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+ - GnLOLot/MiniCPM5-1B-Claude-Opus-Fable5-V2-Thinking
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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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+ # zoder-merged
 
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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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  ## 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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+ * [openbmb/MiniCPM5-1B](https://huggingface.co/openbmb/MiniCPM5-1B)
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+ * [GnLOLot/MiniCPM5-1B-Claude-Opus-Fable5-V2-Thinking](https://huggingface.co/GnLOLot/MiniCPM5-1B-Claude-Opus-Fable5-V2-Thinking)
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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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+ slices:
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+ - sources:
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+ - model: openbmb/MiniCPM5-1B
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+ layer_range: [0, 24]
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+ - model: GnLOLot/MiniCPM5-1B-Claude-Opus-Fable5-V2-Thinking
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+ layer_range: [0, 24]
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+ merge_method: slerp
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+ base_model: openbmb/MiniCPM5-1B
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+ parameters:
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+ t:
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+ - filter: self_attn
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+ value: [0, 0.5, 0.3, 0.7, 1]
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+ - filter: mlp
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+ value: [1, 0.5, 0.7, 0.3, 0]
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+ - value: 0.5
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+ dtype: float16
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  ```