Comments (1)
I've found that the problem here is Quantization:
import torch
from transformers import BitsAndBytesConfig
config = BitsAndBytesConfig(
load_in_4bit=True,
bnb_4bit_quant_type="nf4",
# llm_int8_has_fp16_weight = True,
bnb_4bit_use_double_quant=True,
bnb_4bit_compute_dtype=torch.bfloat16,
)
model = AutoModelForCausalLM.from_pretrained(model_name,
trust_remote_code=True,
quantization_config=config,
device_map="auto"
)
Model gives the error above, but it works without quantization.
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