Altworld/Astrea-R8-Chat-9B-GGUF

🤗 Hugging Face 来源text-generationapache-2.0激活 9B29 GBGGUF✓ 4 个校验和今天更新
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在你的模型文件夹旁边运行它。它会制作种子、将文件与 Hugging Face 比对,然后提交。你只需开始做种,并粘贴你账户中的密钥。它只读取你的文件,绝不修改。如果愿意,可以先阅读脚本。

curl -fsSL https://pirateface.co/package.sh | bash -s -- --repo Altworld/Astrea-R8-Chat-9B-GGUF ./model-folder
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Astrea R8 Chat 9B — GGUF

Official text-only GGUF builds of Altworld/Astrea-R8-Chat-9B, a compact conversational and creative-writing model built on Qwen3.5-9B.

Try Astrea · API · Documentation

Files

Quant Size Use case
Q5_K_M 6.02 GiB Recommended balance of quality and size
Q4_K_M 5.24 GiB Smaller and faster; passed the same chat-routing smoke tests
Q6_K 6.85 GiB Higher fidelity
Q8_0 8.87 GiB Highest-fidelity quant in this repository

These are single-file, text-only models. The inherited vision components are not included because Astrea's visual behavior was not part of the release evaluation.

Run with llama.cpp

Use a current build of llama.cpp; Qwen3.5 support is recent.

llama-cli \
  -hf Altworld/Astrea-R8-Chat-9B-GGUF:Q5_K_M \
  -cnv \
  --reasoning off \
  --temp 0.8 \
  --min-p 0.025 \
  --repeat-penalty 1.08

For an OpenAI-compatible local server:

llama-server \
  -hf Altworld/Astrea-R8-Chat-9B-GGUF:Q5_K_M \
  --reasoning off \
  --temp 0.8 \
  --min-p 0.025 \
  --repeat-penalty 1.08

Use --temp 0.2 for factual chat. The model carries its official chat template inside the GGUF and does not require a system prompt. Reasoning is disabled in the examples because Astrea's release behavior is direct response without a visible thinking block.

Validation

Each file was loaded and generated from with llama.cpp. The checks covered:

  • bare greeting with no system prompt;
  • native Astrea/Altworld identity;
  • ordinary factual chat;
  • supportive conversation;
  • creative-writing routing from a plain request with no scene card;
  • multi-turn recall using the embedded chat template.

Q4_K_M, the most aggressive quant here, correctly answered Good afternoon. as normal chat and produced a coherent story from Write a short story about a dragon who collects spoons. Q5_K_M correctly recalled a name across turns.

The GGUFs declare the base architecture's 262,144-token context. Actual usable context depends on your hardware, llama.cpp build, and runtime settings.

Conversion details

Converted from the official merged BF16 release with llama.cpp commit 76f46ad. The source checkpoint contains no MTP tensors, so conversion used --no-mtp. Quantization used llama.cpp's Q4_K_M, Q5_K_M, Q6_K, and Q8_0 presets.

About Astrea

Astrea was trained on top of Qwen3.5-9B using multi-round LoRA supervised fine-tuning, alternating conversational and narrative rounds and checking each round against Altworldbench. See the BF16 model card for benchmarks, methodology, examples, limitations, and the evaluation protocol.

Astrea is English-first and can still hallucinate. Verify high-stakes claims independently. Engine and quantization differences can affect output, so test your own prompts and settings.

License

Apache-2.0. See LICENSE and NOTICE.