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license: apache-2.0
base_model: google/gemma-4-E2B-it
library_name: llama.cpp
pipeline_tag: text-generation
tags:
- gguf
- lora
- adapter
- gemma4
- text-generation
- coding
---
# Gemopus v1 checkpoint-400 GGUF LoRA
Gemopus v1 checkpoint-400 is a GGUF LoRA adapter trained by Disc View / Disc Labs.
This repo contains the checkpoint-400 LoRA adapter only:
```text
Gemopus-v1-e2b-lora.gguf
```
It is not a standalone full model. To run it, load it together with the base model GGUF.
If `Gemopus-v1-e2b-Q4_K_M-merged.gguf` is present in this repository, that file is the standalone merged GGUF and can be loaded directly in LM Studio.
## Base Model
Base architecture/model family:
```text
google/gemma-4-E2B-it
```
Recommended local GGUF base file:
```text
gemma-4-E2B-it-Q4_K_M.gguf
```
## Identity
Gemopus v1 is a Gemma-based model fine-tuned toward a helpful, structured, Claude-like assistant style. It is not Claude, not Anthropic, and not a standalone model without the base model.
Suggested system prompt:
```text
You are Gemopus v1 by Disc View / Disc Labs, a Gemma-based model fine-tuned toward a Claude-like helpful, structured assistant style. Be helpful, accurate, clear, and strong at coding.
```
## llama.cpp Usage
Example:
```bash
llama-server \
--model gemma-4-E2B-it-Q4_K_M.gguf \
--lora Gemopus-v1-e2b-lora.gguf \
--alias gemopus-v1-e2b-lora \
--ctx-size 4096
```
Then call the OpenAI-compatible endpoint:
```text
http://127.0.0.1:8080/v1/chat/completions
```
## Important
If the model answers that it is stock Gemma or trained by Google, then the LoRA adapter is not attached. Make sure both files are loaded together:
```text
base GGUF + Gemopus-v1-e2b-lora.gguf
```
## Training Notes
This is a LoRA fine-tune checkpoint exported to GGUF adapter format. It was trained as Gemopus v1 checkpoint-400 with a focus on clearer instruction following, coding help, and structured answers.
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