Spaces:
Build error
Build error
Update app.py
Browse files
app.py
CHANGED
|
@@ -1,6 +1,4 @@
|
|
| 1 |
import subprocess
|
| 2 |
-
# Installing flash_attn
|
| 3 |
-
subprocess.run('pip install flash-attn --no-build-isolation', env={'FLASH_ATTENTION_SKIP_CUDA_BUILD': "TRUE"}, shell=True)
|
| 4 |
|
| 5 |
import gradio as gr
|
| 6 |
from PIL import Image
|
|
@@ -13,9 +11,9 @@ import torch
|
|
| 13 |
import spaces
|
| 14 |
|
| 15 |
model_id = "microsoft/Phi-3-vision-128k-instruct"
|
| 16 |
-
model = AutoModelForCausalLM.from_pretrained(model_id, device_map="
|
| 17 |
processor = AutoProcessor.from_pretrained(model_id, trust_remote_code=True)
|
| 18 |
-
model.to("
|
| 19 |
|
| 20 |
PLACEHOLDER = """
|
| 21 |
<div style="padding: 30px; text-align: center; display: flex; flex-direction: column; align-items: center;">
|
|
@@ -71,7 +69,7 @@ def bot_streaming(message, history):
|
|
| 71 |
print(f"prompt is -\n{conversation}")
|
| 72 |
prompt = processor.tokenizer.apply_chat_template(conversation, tokenize=False, add_generation_prompt=True)
|
| 73 |
image = Image.open(image)
|
| 74 |
-
inputs = processor(prompt, image, return_tensors="pt").to("
|
| 75 |
|
| 76 |
streamer = TextIteratorStreamer(processor, **{"skip_special_tokens": True, "skip_prompt": True, 'clean_up_tokenization_spaces':False,})
|
| 77 |
generation_kwargs = dict(inputs, streamer=streamer, max_new_tokens=1024, do_sample=False, temperature=0.0, eos_token_id=processor.tokenizer.eos_token_id,)
|
|
|
|
| 1 |
import subprocess
|
|
|
|
|
|
|
| 2 |
|
| 3 |
import gradio as gr
|
| 4 |
from PIL import Image
|
|
|
|
| 11 |
import spaces
|
| 12 |
|
| 13 |
model_id = "microsoft/Phi-3-vision-128k-instruct"
|
| 14 |
+
model = AutoModelForCausalLM.from_pretrained(model_id, device_map="cpu", trust_remote_code=True, torch_dtype="auto")
|
| 15 |
processor = AutoProcessor.from_pretrained(model_id, trust_remote_code=True)
|
| 16 |
+
model.to("cpu")
|
| 17 |
|
| 18 |
PLACEHOLDER = """
|
| 19 |
<div style="padding: 30px; text-align: center; display: flex; flex-direction: column; align-items: center;">
|
|
|
|
| 69 |
print(f"prompt is -\n{conversation}")
|
| 70 |
prompt = processor.tokenizer.apply_chat_template(conversation, tokenize=False, add_generation_prompt=True)
|
| 71 |
image = Image.open(image)
|
| 72 |
+
inputs = processor(prompt, image, return_tensors="pt").to("cpu")
|
| 73 |
|
| 74 |
streamer = TextIteratorStreamer(processor, **{"skip_special_tokens": True, "skip_prompt": True, 'clean_up_tokenization_spaces':False,})
|
| 75 |
generation_kwargs = dict(inputs, streamer=streamer, max_new_tokens=1024, do_sample=False, temperature=0.0, eos_token_id=processor.tokenizer.eos_token_id,)
|