Phi-4 OpenVINO INT4 Model
Note: This is unoffical version,just for test and dev.
This is the OpenVINO format INT 4 quantized version of the Microsoft Phi-4 . You can use it with the Intel OpenVINO SDK.
optimum-cli export openvino --model .\Your Phi-4 path --task text-generation-with-past --weight-format int4 --sym --group-size 128 --ratio 0.6 --sym --trust-remote-code .\Your output Phi-4 OpenVINO location
Sample Code
from transformers import AutoConfig, AutoTokenizer
from optimum.intel.openvino import OVModelForCausalLM
model_dir = 'Your Phi-4 OpenVINO Path'
ov_config = {"PERFORMANCE_HINT": "LATENCY", "NUM_STREAMS": "1", "CACHE_DIR": ""}
ov_model = OVModelForCausalLM.from_pretrained(
model_dir,
device='GPU',
ov_config=ov_config,
config=AutoConfig.from_pretrained(model_dir, trust_remote_code=True),
trust_remote_code=True,
)
tok = AutoTokenizer.from_pretrained(model_dir, trust_remote_code=True)
tokenizer_kwargs = {"add_special_tokens": False}
prompt = "<|user|>\nI have $20,000 in my savings account, where I receive a 4% profit per year and payments twice a year. Can you please tell me how long it will take for me to become a millionaire? Also, can you please explain the math step by step as if you were explaining it to an uneducated person?\n<|end|><|assistant|>\n"
input_tokens = tok(prompt, return_tensors="pt", **tokenizer_kwargs)
answer = ov_model.generate(**input_tokens, max_new_tokens=1024)
tok.batch_decode(answer, skip_special_tokens=True)[0]
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