Spaces:
Running
on
Zero
Running
on
Zero
VictorSanh
commited on
Commit
•
a7d545f
1
Parent(s):
5e5d5d1
add 286 mix6 table
Browse files- app_dialogue.py +11 -4
app_dialogue.py
CHANGED
@@ -25,20 +25,27 @@ subprocess.run('pip install flash-attn --no-build-isolation', env={'FLASH_ATTENT
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DEVICE = torch.device("cuda")
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MODELS = {
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-
"
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"HuggingFaceM4/idefics2",
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trust_remote_code=True,
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torch_dtype=torch.bfloat16,
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token=os.environ["HF_AUTH_TOKEN"],
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revision="1e05755c1c5cb2077a0f60b83ea1368c22a17282",
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).to(DEVICE),
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-
"
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"HuggingFaceM4/idefics2",
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trust_remote_code=True,
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torch_dtype=torch.bfloat16,
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token=os.environ["HF_AUTH_TOKEN"],
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revision="5cd3c3a3eb5e0ea664f5ac09e73c9ef42da93a86",
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).to(DEVICE),
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}
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PROCESSOR = AutoProcessor.from_pretrained(
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"HuggingFaceM4/idefics2",
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@@ -331,7 +338,7 @@ with gr.Blocks(title="IDEFICS Playground", theme=gr.themes.Base()) as demo:
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with gr.Row(elem_id="model_selector_row"):
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model_selector = gr.Dropdown(
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choices=MODELS.keys(),
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-
value="
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interactive=True,
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show_label=False,
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container=False,
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@@ -520,7 +527,7 @@ with gr.Blocks(title="IDEFICS Playground", theme=gr.themes.Base()) as demo:
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Same as `model_inference` but in greedy mode and with the 80b-instruct.
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Specifically for pre-computing the default examples.
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"""
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-
model_selector = "
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user_prompt_str = message
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chat_history = []
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max_new_tokens = 512
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DEVICE = torch.device("cuda")
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MODELS = {
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+
"284 - neftune - opt 18'500": AutoModelForCausalLM.from_pretrained(
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"HuggingFaceM4/idefics2",
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trust_remote_code=True,
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torch_dtype=torch.bfloat16,
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token=os.environ["HF_AUTH_TOKEN"],
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revision="1e05755c1c5cb2077a0f60b83ea1368c22a17282",
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).to(DEVICE),
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+
"279bis - baseline - opt 18'500": AutoModelForCausalLM.from_pretrained(
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"HuggingFaceM4/idefics2",
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trust_remote_code=True,
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torch_dtype=torch.bfloat16,
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token=os.environ["HF_AUTH_TOKEN"],
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revision="5cd3c3a3eb5e0ea664f5ac09e73c9ef42da93a86",
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).to(DEVICE),
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+
"286 - mix6 tables - opt 20'000": AutoModelForCausalLM.from_pretrained(
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"HuggingFaceM4/idefics2",
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trust_remote_code=True,
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torch_dtype=torch.bfloat16,
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+
token=os.environ["HF_AUTH_TOKEN"],
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revision="b473d49caa964991b40b79fe7cb27d51d4d023f6",
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).to(DEVICE),
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}
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PROCESSOR = AutoProcessor.from_pretrained(
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"HuggingFaceM4/idefics2",
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with gr.Row(elem_id="model_selector_row"):
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model_selector = gr.Dropdown(
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choices=MODELS.keys(),
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+
value="284 - neftune - opt 18'500",
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interactive=True,
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show_label=False,
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container=False,
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Same as `model_inference` but in greedy mode and with the 80b-instruct.
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Specifically for pre-computing the default examples.
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"""
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+
model_selector = "284 - neftune - opt 18'500"
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user_prompt_str = message
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chat_history = []
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max_new_tokens = 512
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