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license: apache-2.0
base_model: Altworld/Astrea-R8-Chat-9B
base_model_relation: quantized
pipeline_tag: image-text-to-text
library_name: transformers
language:
- en
tags:
- qwen3.5
- chat
- creative-writing
- altworld
- fp8
- compressed-tensors
---
# Altworld Astrea R8 Chat 9B — FP8
This is the portable FP8 release of
[Altworld/Astrea-R8-Chat-9B](https://huggingface.co/Altworld/Astrea-R8-Chat-9B),
Altworld's open 9B creative-writing and chat model.
**[Try Astrea](https://chat.altworld.io)** ·
**[API](https://altworld.io/developer)** ·
**[Documentation](https://astrea.altworld.io/docs/)**
The checkpoint uses LLM Compressor's `compressed-tensors` format and can be
served directly by compatible versions of vLLM. It contains six safetensor
shards totalling 11.09 GiB, compared with 17.53 GiB for the BF16 weights.
## Quantization
The checkpoint was generated from the released merged BF16 model with:
- LLM Compressor 0.12.0;
- compressed-tensors 0.17.1;
- `FP8_DYNAMIC`, using E4M3 weights and BF16 per-output-channel scales;
- dynamic per-token FP8 activation quantization at inference time;
- data-free round-to-nearest post-training quantization.
All 248 two-dimensional language-model linear weights are stored in FP8. The
following sensitive or non-linear components remain in BF16:
- input token embeddings;
- `lm_head`;
- Qwen3.5 linear-attention convolution kernels;
- the complete vision tower.
No calibration or training dataset was used during conversion.
## Running with vLLM
Use a recent vLLM release with `compressed-tensors` support and an accelerator
with supported FP8 kernels:
```bash
vllm serve Altworld/Astrea-R8-Chat-9B-FP8 \
--max-model-len 32768 \
--gpu-memory-utilization 0.90
```
The quantization configuration is embedded in `config.json`; no separate
`--quantization` argument should be necessary.
Recommended sampling for writing:
```json
{
"temperature": 0.8,
"min_p": 0.025,
"repetition_penalty": 1.08
}
```
Use `temperature: 0.2` for ordinary factual chat. The bundled chat template
works without a system prompt and defaults to hidden thinking.
## Validation
Before upload, this artifact passed the following local checks:
- every original tensor is present with the expected shape;
- all 248 targeted weights are E4M3 with matching BF16 channel scales;
- all excluded components retain their original BF16 dtype;
- the sharded safetensor index exactly matches all 1,008 stored tensors;
- `AutoConfig`, `AutoTokenizer`, and `AutoProcessor` load successfully;
- `Qwen3_5ForConditionalGeneration` loads the compressed checkpoint and
completes a text-generation smoke test.
The local Transformers smoke test dequantizes weights for its CPU fallback and
therefore does not measure FP8 serving speed. Quantization changes model
numerics, so applications should evaluate this checkpoint on their own prompts
before replacing the BF16 release. Quant-specific Altworldbench results are not
claimed on this card.
## Model quality and limitations
See the [BF16 model card](https://huggingface.co/Altworld/Astrea-R8-Chat-9B)
for training lineage, benchmark methodology, samples, usage guidance, and
limitations. In particular:
- Astrea is text-first; inherited vision behavior was not part of its release
evaluation;
- English dominates training and evaluation;
- outputs can be confidently wrong and must not be treated as authoritative in
high-stakes settings.
## License
Apache-2.0, matching the source model. See `LICENSE` and `NOTICE`.
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