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Model: jbomdev/AlterEgo-GGUF
Source: Original Platform

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README.md

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+---
+license: apache-2.0
+base_model: jbomdev/AlterEgo
+language:
+- en
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+- gguf
+- llama.cpp
+- ollama
+- text-generation
+- from-scratch
+- chatml
+---
+
+<div align="center">
+
+# 🧠 AlterEgo-373M - GGUF
+
+**GGUF builds of a 373M language model designed, trained, and served entirely from scratch.**
+
+[![Model](https://img.shields.io/badge/🤗-Original%20model-yellow)](https://huggingface.co/jbomdev/AlterEgo)
+[![Code](https://img.shields.io/badge/GitHub-AlterEgo%20(training)-181717?logo=github)](https://github.com/J-bom/AlterEgo)
+[![Platform](https://img.shields.io/badge/GitHub-LLME%20(platform)-181717?logo=github)](https://github.com/J-bom/LLME)
+[![Params](https://img.shields.io/badge/params-373M-green)]()
+
+</div>
+
+---
+
+GGUF quantizations of [**jbomdev/AlterEgo**](https://huggingface.co/jbomdev/AlterEgo), a 373M-parameter decoder-only model built from the ground up: architecture, training, tokenizer, and inference all written from scratch. For the full story, including architecture, training curves, hyperparameters, and benchmarks, see the [main model card](https://huggingface.co/jbomdev/AlterEgo).
+
+## Run it with Ollama (one command)
+
+```bash
+ollama run hf.co/jbomdev/AlterEgo-GGUF:Q8_0
+```
+
+Swap the tag for any quant in the table (`:Q4_K_M`, `:F16`). The ChatML template, stop tokens, and sampling defaults are applied automatically from the GGUF metadata and the `params` file in this repo.
+
+## Run it with llama.cpp
+
+```bash
+llama-cli -hf jbomdev/AlterEgo-GGUF:Q8_0 -p "Tell me about the ocean."
+```
+
+## Quantizations
+
+| File | Quant | Size | Notes |
+|---|---|---|---|
+| `alterego-Q8_0.gguf` | Q8_0 | ~0.4 GB | **Recommended.** Near-lossless, still tiny. |
+| `alterego-Q4_K_M.gguf` | Q4_K_M | ~0.25 GB | Smallest. Some quality loss, more noticeable on a model this small. |
+| `alterego-F16.gguf` | F16 | ~0.75 GB | Full precision, max quality. |
+
+AlterEgo is small enough that Q8_0 (or even F16) runs comfortably on any laptop, and at this scale those preserve quality better than aggressive 4-bit quantization. Reach for Q4_K_M only if you want the smallest possible download.
+
+## Recommended generation settings
+
+These are the defaults AlterEgo was tuned and served with in LLME:
+
+| Parameter | Value |
+|---|---|
+| `temperature` | 0.7 |
+| `top_k` | 50 |
+| `top_p` | 1.0 |
+| `repeat_penalty` | 1.1 |
+
+## Chat format
+
+AlterEgo uses **ChatML**, and stops on `<|im_end|>` or `<|endoftext|>`:
+
+```
+<|im_start|>system
+{system prompt}<|im_end|>
+<|im_start|>user
+{message}<|im_end|>
+<|im_start|>assistant
+```
+
+## Limitations
+
+A 373M model on a modest token budget behaves like one: it can be factually wrong, repeat itself, and lose coherence on long prompts. English only. Not safety- or preference-tuned. See the [main model card](https://huggingface.co/jbomdev/AlterEgo#limitations) for details.
+
+## License
+
+Apache 2.0, same as the [base model](https://huggingface.co/jbomdev/AlterEgo).

alterego-F16.gguf

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alterego-Q4_K_M.gguf

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alterego-Q8_0.gguf

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params

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+{
+  "stop": ["<|im_end|>", "<|endoftext|>"],
+  "temperature": 0.7,
+  "top_k": 50,
+  "top_p": 1.0,
+  "repeat_penalty": 1.1,
+  "num_ctx": 2048
+}

system

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+You are Alter Ego, a small AI built from scratch. You're casual and direct. You're not great with facts, math, or current events. When you don't know something, just say so. You're better at chatting than at answering questions.