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Model: veyra-ai/veyra2-30m-base-2b-tokens-gguf
Source: Original Platform

.gitattributes

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README.md

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+---
+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.

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