base_model:
- huihui-ai/Qwen2.5-72B-Instruct-abliterated
Bog standard fp8 w8a8 quant of huihui-ai/Qwen2.5-72B-Instruct-abliterated for datagen purposes.
Recipe:
from transformers import AutoTokenizer, AutoModelForCausalLM
MODEL_ID = "huihui-ai/Qwen2.5-72B-Instruct-abliterated"
model = AutoModelForCausalLM.from_pretrained(MODEL_ID, torch_dtype="auto")
tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
from llmcompressor import oneshot
from llmcompressor.modifiers.quantization import QuantizationModifier
# Configure the simple PTQ quantization
recipe = QuantizationModifier(
targets="Linear", scheme="FP8_DYNAMIC", ignore=["lm_head"])
# Apply the quantization algorithm.
oneshot(model=model, recipe=recipe)
# Save the model.
SAVE_DIR = MODEL_ID.rstrip("/").split("/")[-1] + "-FP8-Dynamic"
model.save_pretrained(SAVE_DIR)
tokenizer.save_pretrained(SAVE_DIR)