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alexliap/Sophea-Genesis-1-FP8-dynamic
Sophea-Genesis-1-FP8-dynamic is a text generation model from alexliap. Use it when you need the model to write or continue text. The card lists the license as apache-2.0.
FP8 (W8A8-dynamic) quantization of KIEFERSA/Sophea-Genesis-1, produced with LLM Compressor.
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From the Hugging Face model README
FP8 (W8A8-dynamic) quantization of KIEFERSA/Sophea-Genesis-1, produced with LLM Compressor.
Weights are quantized to float8_e4m3fn per-channel; activations are quantized to FP8 per-token,
dynamically, at inference time. No calibration data was used: FP8-dynamic derives weight scales
directly from the weights.
compressed-tensorsSophea-Genesis-1 is a hybrid model: 64 decoder layers, of which 48 are Mamba-style linear-attention
layers and 16 are full self-attention, plus a vision tower. To preserve accuracy, the following are
kept in bfloat16 and excluded from quantization:
lm_headlinear_attn.in_proj_a / linear_attn.in_proj_b in every linear-attention layer: these produce
the SSM's decay/step control signals. Quantization error here compounds along the recurrent state
across the sequence rather than staying local, so they're left unquantized despite being Linear
layers.model.visual.* (the vision tower): untouched, this checkpoint was not calibrated for vision input.All other Linear layers (self-attention q/k/v/o, linear-attention qkv/z/out projections, and MLP
gate/up/down, across all 64 layers) are FP8.
vllm serve alexliap/Sophea-Genesis-1-FP8-dynamic
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained(
"alexliap/Sophea-Genesis-1-FP8-dynamic", device_map="auto"
)
tokenizer = AutoTokenizer.from_pretrained("alexliap/Sophea-Genesis-1-FP8-dynamic")
LLM Compressor v0.13.0, FP8_DYNAMIC scheme.
from llmcompressor.modifiers.quantization import QuantizationModifier
QuantizationModifier(
targets=["Linear"],
scheme="FP8_DYNAMIC",
ignore=[
"lm_head",
r"re:.*linear_attn\.in_proj_a$",
r"re:.*linear_attn\.in_proj_b$",
r"re:model\.visual\..*",
],
)
Apache-2.0, inherited from the base model.