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1442fb8
1
Parent(s):
cf0a724
ui: Add system features
Browse filesAdd a list of interesting detected system features, plus an expandable
table (hidden by default) that includes more debug information.
Signed-off-by: James O. D. Hunt <james.o.hunt@intel.com>
- app.py +168 -8
- requirements.txt +13 -2
app.py
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@@ -1,35 +1,195 @@
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from transformers import AutoModel, AutoTokenizer, LlamaTokenizer, LlamaForCausalLM
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import gradio as gr
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import torch
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DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
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-
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-
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model = model.eval()
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def predict(input, history=None):
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if history is None:
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history = []
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new_user_input_ids = tokenizer.encode(
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bot_input_ids = torch.cat([torch.LongTensor(history), new_user_input_ids], dim=-1)
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history = model.generate(
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# convert the tokens to text, and then split the responses into the right format
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response = tokenizer.decode(history[0]).split("<|endoftext|>")
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response = [
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return response, history
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with gr.Blocks() as demo:
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gr.Markdown(
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-
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state = gr.State([])
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chatbot = gr.Chatbot([], elem_id="chatbot").style(height=400)
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with gr.Row():
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with gr.Column(scale=4):
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txt = gr.Textbox(
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with gr.Column(scale=1):
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button = gr.Button("Generate")
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txt.submit(predict, [txt, state], [chatbot, state])
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button.click(predict, [txt, state], [chatbot, state])
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demo.queue().launch(share=True, server_name="0.0.0.0")
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from transformers import AutoModel, AutoTokenizer, LlamaTokenizer, LlamaForCausalLM
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import gradio as gr
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import torch
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import os
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import io
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import sys
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import platform
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import intel_extension_for_pytorch as ipex
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import intel_extension_for_pytorch._C as ipex_core
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from cpuinfo import get_cpu_info
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from contextlib import redirect_stdout
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DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
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ROOT = '/'
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SELF_ROOT = '/proc/self/root'
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tokenizer = LlamaTokenizer.from_pretrained(
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"lmsys/vicuna-7b-v1.3", trust_remote_code=True
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)
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model = LlamaForCausalLM.from_pretrained(
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"lmsys/vicuna-7b-v1.3", trust_remote_code=True
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).to(DEVICE)
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model = model.eval()
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def in_chroot():
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'''
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Return true if running in a chroot environment.
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'''
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try:
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root_stat = os.stat(ROOT)
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self_stat = os.stat(SELF_ROOT)
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except FileNotFoundError as e:
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sys.exit(f"ERROR: Failed to stat: {e}")
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root_inode = root_stat.st_ino
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self_inode = self_stat.st_ino
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# Inode 2 is the root inode for most filesystems.
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# However, XFS uses 128 for root.
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if root_inode not in [2, 128]:
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return True
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return not (root_inode == self_inode)
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def get_features():
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'''
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Returns a dictionary of all feature:
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key: feature name.
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value: Boolean showing if feature available.
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'''
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cpu_info = get_cpu_info()
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flags = cpu_info["flags"]
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detect_ipex_amx_enabled = lambda: ipex_core._get_current_isa_level() == 'AMX'
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detect_ipex_amx_available = (
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lambda: ipex_core._get_highest_cpu_support_isa_level() == 'AMX'
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)
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features = {
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'VM': 'hypervisor' in flags,
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'TDX TD': 'tdx_guest' in flags,
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'AMX available': 'amx_tile' in flags,
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'AMX-BF16 available': 'amx_bf16' in flags,
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'AMX-INT8 available': 'amx_int8' in flags,
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'AVX-VNNI available': 'avx_vnni' in flags,
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'AVX512-VNNI available': 'avx512_vnni' in flags,
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'AVX512-FP16 available': 'avx512_fp16' in flags,
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'AVX512-BF16 available': 'avx512_bf16' in flags,
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'AMX IPEX available': detect_ipex_amx_available(),
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'AMX IPEX enabled': detect_ipex_amx_enabled(),
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}
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return features
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def get_debug_details():
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'''
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Return a block of markdown text that shows useful debug
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information.
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'''
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# ipex.version() prints to stdout, so redirect stdout to
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# capture the output.
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buffer = io.StringIO()
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with redirect_stdout(buffer):
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ipex.version()
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ipex_version_details = buffer.getvalue().replace("\n", ", ")
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ipex_current_isa_level = ipex_core._get_current_isa_level()
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ipex_max_isa_level = ipex_core._get_highest_cpu_support_isa_level()
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ipex_env_var = os.getenv('ATEN_CPU_CAPABILITY')
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onednn_env_var = os.getenv('ONEDNN_MAX_CPU_ISA')
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in_chroot_result = in_chroot()
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cpu_info = get_cpu_info()
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flags = cpu_info["flags"]
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# Note that rather than using `<details>`, we could use gradio.Accordian(),
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# but the markdown version is more visually compact.
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md = f"""
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<details>
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<summary>Click to show debug details</summary>
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| Feature | Value |
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|-|-|
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| Arch | `{cpu_info['arch']}` |
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| CPU | `{cpu_info['brand_raw']}` |
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| CPU flags | `{flags}` |
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| Python version | `{sys.version}` (implementation: `{platform.python_implementation()}`) |
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| Python version details | `{sys.version_info}` |
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| PyTorch version | `{torch.__version__}` |
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| IPEX version | `{ipex.ipex_version}` |
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| IPEX CPU detected | `{ipex_core._has_cpu()}` |
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| IPEX XPU detected | `{ipex_core._has_xpu()}` |
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| IPEX version details | `{ipex_version_details}` |
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| IPEX env var `ATEN_CPU_CAPABILITY` | `{ipex_env_var}` |
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| IPEX current ISA level | `{ipex_current_isa_level}` |
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| IPEX max ISA level | `{ipex_max_isa_level}` |
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| oneDNN env var `ONEDNN_MAX_CPU_ISA` | `{onednn_env_var}` |
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| in chroot | `{in_chroot_result}` |
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</details>
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"""
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return md
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def predict(input, history=None):
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if history is None:
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history = []
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new_user_input_ids = tokenizer.encode(
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input + tokenizer.eos_token, return_tensors='pt'
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)
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bot_input_ids = torch.cat([torch.LongTensor(history), new_user_input_ids], dim=-1)
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history = model.generate(
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bot_input_ids, max_length=1000, pad_token_id=tokenizer.eos_token_id
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).tolist()
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# convert the tokens to text, and then split the responses into the right format
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response = tokenizer.decode(history[0]).split("<|endoftext|>")
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response = [
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(response[i], response[i + 1]) for i in range(0, len(response) - 1, 2)
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] # convert to tuples of list
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return response, history
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with gr.Blocks() as demo:
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gr.Markdown(
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'''## Confidential HuggingFace Runner
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'''
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)
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state = gr.State([])
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chatbot = gr.Chatbot([], elem_id="chatbot").style(height=400)
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with gr.Row():
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with gr.Column(scale=4):
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txt = gr.Textbox(
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show_label=False, placeholder="Enter text and press enter"
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).style(container=False)
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with gr.Column(scale=1):
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button = gr.Button("Generate")
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txt.submit(predict, [txt, state], [chatbot, state])
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button.click(predict, [txt, state], [chatbot, state])
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with gr.Row():
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features_dict = get_features()
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all_features = features_dict.keys()
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# Get a list of feature names that are actually set/available
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set_features = [key for key in features_dict if features_dict[key]]
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gr.CheckboxGroup(
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all_features,
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label="Features",
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# Make the boxes read-only
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interactive=False,
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# Specify which features were detected
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value=set_features,
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info="Features detected from environment",
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)
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with gr.Row():
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debug_details = get_debug_details()
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gr.Markdown(debug_details)
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demo.queue().launch(share=True, server_name="0.0.0.0")
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requirements.txt
CHANGED
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@@ -1,6 +1,17 @@
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-
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cpm_kernels
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icetk
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gradio==3.50.2
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accelerate
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git+https://github.com/huggingface/transformers
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# For pytorch
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--find-links https://download.pytorch.org/whl/torch_stable.html
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# For ipex
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--trusted-host pytorch-extension.intel.com
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--extra-index-url http://pytorch-extension.intel.com/release-whl/stable/cpu/us/intel-extension-for-pytorchtorch
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cpm_kernels
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icetk
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gradio==3.50.2
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accelerate
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git+https://github.com/huggingface/transformers
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py-cpuinfo
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# Versions must match
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torch==2.3.0+cpu
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intel-extension-for-pytorch==2.3.0
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