Update app.py
Browse files
app.py
CHANGED
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@@ -76,7 +76,7 @@ class CustomTrainerCallback(TrainerCallback):
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job.progress = 0.1 + (prog * 0.8)
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if state.global_step % 1 == 0:
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loss = state.log_history[-1].get('loss', 'N/A') if state.log_history else '...'
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job.add_log(f"Step {state.global_step}/{state.max_steps} | Loss: {loss}")
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return control
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def on_save(self, args, state, control, **kwargs):
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@@ -236,7 +236,7 @@ def background_train_task(job_id, hf_token, model_name, new_repo_name, lora_r, l
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report_to="none",
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fp16=True if torch.cuda.is_available() else False,
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disable_tqdm=True,
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dataloader_num_workers=
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dataloader_pin_memory=True,
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torch_compile=True if os.name == 'posix' else False
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)
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@@ -361,7 +361,7 @@ def load_from_url(request: gr.Request):
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pass
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return gr.update(selected="launch_tab"), ""
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with gr.Blocks(title="Nucleus Enterprise"):
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with gr.Column():
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gr.Markdown("# ⚛️ NUCLEUS ENTERPRISE")
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gr.Markdown("Autonomous LLM Foundry | V5.0 Stable")
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job.progress = 0.1 + (prog * 0.8)
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if state.global_step % 1 == 0:
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loss = state.log_history[-1].get('loss', 'N/A') if state.log_history else '...'
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job.add_log(f"Training Step {state.global_step}/{state.max_steps} | Loss: {loss}")
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return control
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def on_save(self, args, state, control, **kwargs):
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report_to="none",
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fp16=True if torch.cuda.is_available() else False,
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disable_tqdm=True,
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dataloader_num_workers=4,
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dataloader_pin_memory=True,
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torch_compile=True if os.name == 'posix' else False
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)
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pass
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return gr.update(selected="launch_tab"), ""
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with gr.Blocks(title="Nucleus Enterprise") as demo:
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with gr.Column():
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gr.Markdown("# ⚛️ NUCLEUS ENTERPRISE")
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gr.Markdown("Autonomous LLM Foundry | V5.0 Stable")
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