---
license: apache-2.0
base_model: veyra-ai/veyra2-30m-base-2b-tokens
tags:
- gguf
- llama.cpp
- text-generation
- veyra
- small-language-model
---

# Veyra2 30M Base 2B Tokens GGUF

GGUF conversions of [`veyra-ai/veyra2-30m-base-2b-tokens`](https://huggingface.co/veyra-ai/veyra2-30m-base-2b-tokens) for llama.cpp-compatible runtimes.

## Files

- `veyra2-30m-base-2b-tokens-f16.gguf`
- `veyra2-30m-base-2b-tokens-Q8_0.gguf`
- `veyra2-30m-base-2b-tokens-Q6_K.gguf`
- `veyra2-30m-base-2b-tokens-Q5_K_M.gguf`
- `veyra2-30m-base-2b-tokens-Q4_K_M.gguf`
- `veyra2-30m-base-2b-tokens-Q3_K_M.gguf`
- `veyra2-30m-base-2b-tokens-Q2_K.gguf`

## Notes

These GGUFs were converted with `tokenizer.ggml.add_eos_token=false`, because the original conversion metadata appended EOS to prompts, causing llama.cpp continuation prompts to behave like a new document after the prompt. If you are using something like LM Studio you can set your chat template to ChatML to talk to Veyra. 

Recommended starting points:

- Best quality: `Q8_0` or `f16`
- Balanced: `Q5_K_M` or `Q6_K`
- Smallest experimental: `Q2_K` / `Q3_K_M`

Recommended settings:

- Temperature: 0.8
- Repeat Penalty: 1.2

**Note:** For lower quants I would recommend using higher temperature to avoid repetition over repeat penalty.