Browsing: Tutorial

In this tutorial, we build an end-to-end NVIDIA NeMo AutoModel workflow in Google Colab and use a single GPU to explore the same configuration-driven training architecture…

import torch.nn as nn import torch.nn.functional as F from dataclasses import dataclass torch.manual_seed(0) @dataclass class Cfg: d_model: int = 192 n_head: int = 6 n_layer: int…

print(“\n[5/10] Creating a synthetic multimodal report…”) monthly_data = pd.DataFrame( { “Month”: [“Jan”, “Feb”, “Mar”, “Apr”, “May”, “Jun”], “Query Volume”: [1200, 1700, 2100, 2600, 3300, 4100], “Hybrid…

def _purge(*prefixes): for name in [m for m in list(sys.modules) if any(m == p or m.startswith(p + “.”) for p in prefixes)]: del sys.modules[name] def _load_ocrmypdf():…

def extract_function_source(full_text, function_name): text = full_text.replace(“\r\n”, “\n”) fence = re.search(r”“`(?:python)?\n(.*?)“`”, text, flags=re.S | re.I) if fence: text = fence.group(1) pattern = rf”^def\s+{re.escape(function_name)}\s*\(” match = re.search(pattern, text,…

print(“\n” + “=” * 90) print(“[5] cuTile kernels are defined only if cuda.tile imports successfully”) print(“=” * 90) if cutile_import_ok: ConstInt = ct.Constant[int] @ct.kernel def cutile_vec_add_direct_kernel(a,…

print(“\n########## 5. ANALYSIS ##########”) import numpy as np, pandas as pd def find_latest_report(): cands = [] for base in [os.path.expanduser(“~/.local/share/garak/garak_runs”), os.path.expanduser(“~/.cache/garak”), “.”]: cands += glob.glob(os.path.join(base, “**”,…

mock_server_code = r”’ from fastapi import FastAPI, Request import time app = FastAPI() STATE = {“calls”: 0} @app.post(“/v1/chat/completions”) async def chat_completions(request: Request): payload = await request.json()…

In this tutorial, we work through an end-to-end workflow for Qualcomm AI Hub Models. We start by setting up the required package, discovering the available model…

In this tutorial, we fine-tune Liquid AI’s LFM2 model through a complete open-source workflow. We start by loading the base LFM2 checkpoint with QLoRA, preparing a…