Update README.md
Browse files
README.md
CHANGED
@@ -1,3 +1,48 @@
|
|
1 |
-
---
|
2 |
-
license: mit
|
3 |
-
---
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
license: mit
|
3 |
+
---
|
4 |
+
|
5 |
+
# **Phi-4 OpenVINO INT4 Model**
|
6 |
+
|
7 |
+
<b><span style="text-decoration:underline">Note: This is unoffical version,just for test and dev.</span></b>
|
8 |
+
|
9 |
+
This is the OpenVINO format INT 4 quantized version of the Microsoft Phi-4 . You can use it with the Intel OpenVINO SDK.
|
10 |
+
|
11 |
+
```bash
|
12 |
+
|
13 |
+
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
|
14 |
+
```
|
15 |
+
|
16 |
+
## **Sample Code**
|
17 |
+
|
18 |
+
|
19 |
+
```python
|
20 |
+
|
21 |
+
from transformers import AutoConfig, AutoTokenizer
|
22 |
+
from optimum.intel.openvino import OVModelForCausalLM
|
23 |
+
|
24 |
+
model_dir = 'Your Phi-4 OpenVINO Path'
|
25 |
+
|
26 |
+
ov_config = {"PERFORMANCE_HINT": "LATENCY", "NUM_STREAMS": "1", "CACHE_DIR": ""}
|
27 |
+
|
28 |
+
ov_model = OVModelForCausalLM.from_pretrained(
|
29 |
+
model_dir,
|
30 |
+
device='GPU',
|
31 |
+
ov_config=ov_config,
|
32 |
+
config=AutoConfig.from_pretrained(model_dir, trust_remote_code=True),
|
33 |
+
trust_remote_code=True,
|
34 |
+
)
|
35 |
+
|
36 |
+
tok = AutoTokenizer.from_pretrained(model_dir, trust_remote_code=True)
|
37 |
+
|
38 |
+
tokenizer_kwargs = {"add_special_tokens": False}
|
39 |
+
|
40 |
+
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"
|
41 |
+
|
42 |
+
input_tokens = tok(prompt, return_tensors="pt", **tokenizer_kwargs)
|
43 |
+
|
44 |
+
answer = ov_model.generate(**input_tokens, max_new_tokens=1024)
|
45 |
+
|
46 |
+
tok.batch_decode(answer, skip_special_tokens=True)[0]
|
47 |
+
|
48 |
+
```
|