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z3+u3e+uOcdVlLxN4J9hdnMr2W39YwjjfI6Dz0w0T0LYVjkc\/Wt37qgOTAAu\/l8pxW98wXvhmHKHcltCEgHyBZwsdleGikm3x+tCwaN4i625mJU8vJOfNMIP5WNwFo70riSimlSGDDNYGZP5OoqecTpj4mUZ645SKdoj90XiWzwObwFUe2OcsTVhfNlVVpzZjYFyRmUnTp+\/eo+1Y\/I5M3U+Ii6wYmAkEW+e1GNri9yfo0uAWIIVq2i8bDca+DESmcaRVU3iBVKtvurmh7ojdCmY0i75iQxovncaOL\/sqNcJ5wbgczIowBc6SlVr10AQpq5UmjD3VFGZGuYOR877kUqjimtlC4gWJxpcbEn5uH57c3fekkuM1wqSYrsAsc+jdG9LLCeK92P+zkR1\/JSvoROcxscN+yAu5kODVRQYASBu0JPNAqdysEjBcQBqg74Gt8MjowzU0iz9uo5j+CRy9zJyDEMQ1dSWbE5GZEGGYN\/RdRdTjFRiRCpT5hPc3AP3BZqTsjp38+vkzsAhcQhJQmeWtEel2Wi9qolx8FeVW2RfPRh0XZRh6N2mL1HZiPtEhP48WS20X02nKP8OQ7mpCHIsYz1JJzaGu2vN6O+LkZnOgwZTAEuIaluYEijFjXLiO0EJtZ5mzCXKdzMEqvi1tWUNlgyDQCm4iubArNaen+HHan35gLOhezqPTSPg2qMcalmYEileB6dPs90FH\/ncCOjPrTMO4HtLWNvpVuFE\/T20VAnSyHi9ZfuJk7GAb+RdEY23ldpE4rCPKKZJaoTlLPWdH3VwXf9vSk5L3HCIlvIMSXtXMLJVMzD5SnlC2zvTlbRsyd132emnUEUi5UwyvlcqLKVC9lkpiNVaBHzq4rxDVFCX3UU895FbJEswjZ2Q6bsvCiTSwwA9SentMJqLh4IndOi1qEV2UMp8XIZboPEmItcgKxl4E0eRKNF4e2LJNxo56tFGXKK6at7HNtl8Yumy7oqjzi27QtVF2XN98O5J9rs9AjHAv5NHQ27kZ96TnrFJFt3YifzLu2SYRmGGQylu9Q1MdaC0wt7L7EDYPiMgKueXPuysG0lIAI9hhwULwfD8+tMqLJuViGBqkScsZ+rnf2A1aS++Rb7TRJEl2Tj3MDkWQHH36FZw9fEpvbFfPxTRSYSLFMw+hpQAJ2PtQbBHneTzb7uSdgPBV5eqxx13U7yjHu4999bbHDXvKZOy2h0e9gjhFWPjf3HhFy3RzE6NBgJb7EbfDtxR7zRvnoub09p\/bqLNwpfBzYlC41CUC9YXvgX5jhUK+K96Mw\/kY40d5nHLH6SRLiGEicq3\/86Q9KYygSuKpVHaX8SEVDDBE5F7LCZ6elbNXfqPvlESbyZYqR0Rdt9LZMOhvA+Z9O4izzcLCyTUrhf7xBzxdS24zly7Y3YOvdIe\/cFRQNYHwHcAWoG6EkLnoUXf3zoQLSZMI+DfGJ4FM8eSKnnRcFmhafM5pOvJP2D6Rt+opFheT9unuUSzeWpGaynerovi4i4Xeu+Gtvag8MJbDpOVbmriWph9xMgRkQ5dud4tCPNdWFT2BzFMoCkbu7Oa3cZC\/QjsK+SVzElFhI0wuwkYaKyPfZHgF7aoeiAugoSTpysf7Fx6ddUcHpw4c6J4afVHly9xxgnmTTqCLLXSP22SGYhql1+joKvd\/0TQbI06aVBcMmnhAwjFUW78dvwkNhhY3QWTJ2h4LcB3sl+sURWuXD7SnALOaiYncTtoi1x5uj7IAgIl8SgM8bY27w\/YHvpbvKMJbpNkRVZ5zJ7LuOua4xbhALC2LYlqhL1YGLOJ0EzYNXnB\/eixsu3u7PncNbvEiO1pB5MAB9mlMEiV\/rHjiFZn7gIjq60w3PRDZ5jPMAodsKotzg20bLLNqxuu84MKKG\/dC6fBheLUSEXSlELZJoWRRhrj+\/DDtqFbDmgQa19HoGIH3nask0Pch6bJDxXa4CLpAQqX05kavGPKXO\/heUjaIDjdxnnEIOGiFv5xqMBCa0IUFRF9la26acdUA4UQsV\/BxjXqoRlazYC1gQOh2M9rZjyYB2mkCc5hbKIEgs3F6FXwvZo4mkcisqxATsS4zkRQaPEVHS19fer8\/N598P6jXpHD\/b8703gCGuqI+mBvr2FQEJADGxhUP61ci1ZaLMFEJvOFlbG3Fp0F6N29LGiioyReLWfhxsAP8xiwDgrKpTbnp4a\/X9frtSHmKgM73Z9Dgm4Z9NzlF04W3h15E5Zqtu4k\/FD4EUy4Un35Zg9fAvZatckM5s0\/ESzGcoDDNafAagZw2aWzCZnVUteb98+f1wwXhnI8DwE14OawnQ9fwp1U9BJY8ZtGxbiFvsdV1B+xDm9VB91le3IYU2JecDhVGsSYxew0oNsoh3W\/2OKtauROt+OiF91wF4LRRr\/KaTpGJiVKQiSl\/Gj01W+o79ulQkyZOyP4OV3NFu4P9nH\/P4fkw7DUXZIYDBI9d\/vRFWkMx3FGsc8UX\/jbcZf5vzDtw5i+ZfoinsDBRnGQX8tnjEdpDH43GUN6L50fYBN8EheWFtZLsFS70Y1b9cMGRnzG2k06Myrn6xIZH\/ksK+i3y4Ct\/uworLDrOvLWDkoO0R6Vx0BJ8OPN2k4WC3Nu5doNPH6vtC4c\/6qr\/Nqkhh3d37MorCd5ZbmKFaUrlq8yHuMup8cOKpvnVfT8LVzHQrqvqmctziaadDHNdAzLIf52USG1yCYzvdiqb6YsW2zQ+4NtiznuGQrZel9Wj2gwI\/SPiRhjip+jne21\/xP1vLV1Ems+91QE2Fah3HuGcVLOTFIC+21ibuA3Qhdg9wPTiSiwyDM9CkxmuzRpWna+yOmcSgTNEZJvhoenvM29R88KmAQkSXMM29frbFxxrO551z29oGSaOzCV6Tr8RS5uYdO4KBbw\/zEU3DQ3pQJ\/kBDM7pzc8u1IgXH4miYVhblrwP\/xMWOh\/UCv9VOQmuc1I1Z1Lp7wshowhggpO9RRmEgfloZe1U1zHhAu0UqXLjAKr1RxXGOSlMuHB34NBD3OC4M50c6Bsxj5p8lW0IBOzTb+l6Z\/eEDzzeQEP5hJs5LohavT7CEiQ2+R3dI\/HoADXayknxmZkADyiZaEu9ONxndjDqjvgPSMbwYgg7Uw\/I9X7w4lxWu1\/wefmbIYMrZM1TPp0DYXr1eb\/+hu4VEctB9riAT05vtjhXRG5RLXu7F9QBAvXh1zmi9iTZrPnvNM50wAJiWSsTB6UvEx53nknAigb9pBotm9IUFwJBPfJabfUwTvOk27fBZrOyK\/4jlZvFGcwnidpVaI1pawA2p\/xqhbQrffU7wKZWy1FuXDGQlH387usZs9i9mPxfOokNp+rrVm5BLbnvCaBu5BGwC+AT4W6QkzpJNFFqL+kS3v7rrUJXjfbZabia2VkP1RCXfRlTGIQbWeROokWN4j7l5dL+PkvfH+N0qsxOk6UtzRo7krP0aohSGuPT1O8en+o\/T+7N07Jh\/IxfwErtyzavSf7jYznmUagR+o\/SCGaBH4PBPhzt0+cNBLjlucqRsJDVlYk7\/db62Bk9C2Xbcey1\/nqSgvkJkn4glo4bIa\/lN9pJJjB+Vz\/dVvnw1RDOqNdt4IKiiQ\/n8V322A4FDrtwvaxs1ynWLoYWiuAFcGnYwHDgEdYdyeXPxaipIorwy30UlX4V4B3KYki+HloegthuDhHJUPMBBJn5reuTEIfsB\/JSN3j5drQhgCrG2cZNW9aV8DKgDOhnazJc2LQIYrnH\/1Kr3UsUaFJqVs1hBX2JGOlNIzV48uMFSpT5uShLz2I\/9s8iD4xq58Dfk9bdkZBX5fdQ3b3zHu0L9yZS5oBJrSTr+Cfe0pwhF5ZAsGN6pFeNcW\/wNAa+bZUaopAxI225QH1U1iE5sefxDZUzc5S5rQIXIpCflYLpzHtGMvjZMpH6H+jnj8pCJUOMpel4Em77xy62gNQ4TW5IpJd0Fclu4ktn0V5j64XnjySByOw3yAks16KQp\/+ju6fOpTPkJhLL0RGN0wEvQEZK8CHSYnmn513TunKVM6bFIzf+kKnEU5oucOngdRNPBVVwvTDs\/4\/b67w4lzItaV6JCwp9arxdHOG4keq4uyAkQ2D0lwIAdt93HdoNJDb+srB3uGQNeRmpWQWNXN1wiJdz4SgdcRdvuyt1jlgwHb\/v4BmVV59z1ob6yzQVl1ZW27V4NClyoSOHYP\/EPpqxa3ZOrO6E2qzM\/mq1+UAY7OqNvYEC5m7u5hhIvxXv3RPhok4hP2iWQF2MwWxKjh2A5nknA8p120QQoadymB+mYNZUepqp2EKI+UNfs37cXM\/ZLajZOhxy540kvEhbtx86RQhxTmHRHxum154t+efV0JSRrY6XwMEoa91s5Urv4ddadjMj7+r1VsGk08oizCWetUqpC39xMPqGTKYvhekK41Oe4cnUheyDsZSYFaMIn3Oxjhj2+nw5Dd0gS\/uXc1XJYmodEYrVVKu8yfWZLm6M0YE9FVHFG2YmUQ\/KwlxQQ+3YcT4PxkvR6heVbFWXYNAZqFlKETinttgyejNFo+o3nYpgTw45VDBa+O52R0eSbsNennQV5sMtBl096slo3VXuAJYyKrXUeGZyEx+KWFj2GpWRErRs99SpHuF+rxitxMjKZvUdfF6OOYpI6BO90+72fHj8as06EFsvWmNP5PZCHH0BqJlv12+8j3sz7JLWmLEMOwDmUx1gEUpAciDWr1XXoXmbC48LIrGxu5+eQOgE8jub4fIKy+xFD3LIEeTjFiiCvYk6emDuJ02ZYOH6zxzzB8ntd4yBbCULg1dLcanF0mOlCYKbXithvM0rycVtWCs6if8Wj5EoQceESzFy5crfeWRU8O92u9yjNyg4CaFs8OWhzxa5n+LhrkH83t8iJZC4wZiYXNHStyW\/QJrmbUACqehyabUy00tSosOjyKWVyLvEFjBzXY72B5JqgmUyJE+AW98kcFTd5NR0DfUk8vwatV+qmxeIbg4aIjjj8xUUMJqaYzGwdZdkYZDpwvT+Aem0DC2c1PeSj7jWjj5p6WPhP0TOYFA45LJbYZdBMNeOFF5sCVKx2RPUTzuB+HRRqGyQThykhjZxucaglw+dr5OFBgc0UXLlMr9vVH0cuTh3xPZtn1STCwOaJP7LpA1AbmcelAwJNRKwfZFZsmYu3acwICtBjKBOReAl0Ly2Fuinmc1MUY14m8ORaUd1ml5eU1bFz5Xkum+L3ZxYd5T6KG1k99ATQQc2I2B91cBL1eAlw\/0BW4Hpt3+C7yT0ULG98csv1fevHPsY+dsUm7glNPnGv0yNCWWtvt50rt5VeVhgCRuKrNyZeHX4OLT6d2Tnw20aZAxmzIbAONjwx7XE9K8MmpO\/a1cTOUaI7LxoVp3TjsrlgKAGDzaAXP865j7uH6sXubSMxbuV27aXDH0GnZlN39b3Ab09A3ubylYoA7I19pokTAThI0c\/EI\/intPfJbaPanZ4elzBb+LU8bL\/OlUA2i\/Nvwo+dVf0j18aiWa70L13VKZbdHq5nkSUzNrRjl3c\/q2aGh7O0XSNnX21o4B7QmPLo6kl05itZ+B497+LNcTbz8dZKgG\/pkinQYqR0ZbjvpGTfyjnnVjHVgwsRRJLk5g7\/9FApmmpkzbnOLoTFhKntM985mGDQsdQmrTCWFn0w+ZUkQ2wyDG7CE1LucDKWUDQBKnNT3seXV1SLJ4Y0ETcgGXkm5lkfZ16o\/wsqNqEhCfuTWIYALGCvbzIDdDRSSNi\/hD0XWrOmex6D7+MC9OF6V2iGXqaMEyaBKNJrlmOPd8iWZVoovAU\/kis17n6BNR3Bs\/\/PacxEsgFLKUIALEjFbyxTdT11NgCeoPCqInxmzoaE3U6BdNpSWZcSSI\/2bgoY2YL55F0EZW0YPFeU2dc7Fk5Ip+HkjAj9e8UjgxXmNjXAQGxhFUaaX57WdaLpWmylrJSvSbX2uDftCTUvQak6+2gGYDwaULbvCrHgp80LqIbduCEDgdF11A0QwWjT31a2BTwb+StFSkW9iqibWk+Ty86argU6vfR+afE5LpZYseF0W3K4I0bVfxB1DaZSR2Hi4hQ7W\/vB6w+an++UKRVq2tNnY1rPRIofMr6PaPdLXvXkY+Qa6NMxYsHMm7GyeUPFFfYyYhxZrnt4KXWCBYDnqjtPWseiMCCbi9Db9iP5hsLPFUVGSMIbm1Apy+DA9rpZ6GJH6phCaHkXydPLU1mZgTI57OQvdRgljMPPslauvTT0l0YmTGhIZj8CwfvymJyeyoXTxW0WGa3s2SabxpDkf0gZmbkPrqdd1PSByIWQNQYvUgaSxOl+mEbDzOxDfQmkyia5orjB7Y6F2MB\/wtcWYyyAftKY8LXVd8HadSaVWrir5hcqgWu2H974G2n23ti0SfG2JDqJF10GKe4IQx4n9adl45qWdIdIzIbOOHJ4bQWlT2+c7nVMc0GSE1\/cLR0kzxlSizcHtDc7rKyVu8i0\/sjKxyfpbrYW2lS\/8YUeYrNpiVgySVSUn9XLhYtvA9wmGbgf3iqnK2Mwdnf0yAT1koTJDwQRnq2bWfbHIAEOOD0HbnsAa4qeRnY9LCdEhvZxVN2CGvX4n6oTdDoOSjeNGCHhFr1aqbKdnVpRasELPLtnbdoyh4O7WSjf0Clmk2p8OR\/LNZm9+lvkZeTvx7XOnloV0S9ZrtrzpKB\/UxnLdGcxwes5uREFq8dBP0ueV4EVXmVxRpSHV7l\/lnRhEc+L+vJrOAkg\/mhDnqSV2Mmc25u7rHvo3kqOGB1BX5\/TN2Zq1UMT0Rfl+OXIXVBcQSUz9t4Tr\/1SU65fkfEMXaQnllZdCVltxLW+YCjuutTg7hpaNelT2WUWcKlFZR2JcjF8dnz2uWX0zDvq1qfbgkzhUovGFcZsXNFktcrDDmtMpGo99iyzHPJ6FMzez\/d3M0HlOIiYHEHziE0RtgVbbTgj3GVoksaaawyECDsKf6BKPo8v0j4kKNuwGqVCRaB4FrLO2pV7hDHOCGU7dFXR+iulAKQD8OwgJGzIlgHzM97IGBHFw8ib6QWuZqVP5GgA\/mLp8WN4Q9xbkgj1wz6nIAJR1SHnsI3h5XSNoUHrQQtE\/TqIWd3IdVdmU+NBlqwQsCVbkwQFN7devUIpC9WDOIlhTxgODlIiQCk6H+r5HMSI1u+gHhGkAy7cUbf8aSrwpYDIECIzjdm3OC00e8qGt4oHG6mExpi+tTskKzv8lsFY8oCkHpNlSZMYW4YyeBux+lgwdz1EXLjAAP+Vt1PG5zQGdfp5388sa+drBH2ISxhC\/j77lg6Cg9VFkRP5zlfgba9xA8\/KdhLocry12TN02vB8jA578iG7q+2zXnlg\/nvSY1OK74qB5DpOQNdKwr7ZVKkS+z7ss\/+3phDG+u3e9NOeqy7YnlPYBdLP2QXuP8c08B4xoA4d8ny0x4m4neSQn+yn8qIYP6iqmTf71BnIQyvFtd4BN+l4CHU8bpawIPi4kCL0kZdjMqSh5Ifp5w1OeKb8k\/ntM1H1+MfeIZgc4iPJhOCMF3XCx3u3FYmaDoapWzJDND1yEtZ\/DVVjeX1djT9ECSM1UPWTbM9iAELtV6D49XXh4vrub5mxG8ggz\/+Jqg7QKJQsWyVB5b5o4hQdi3eCZQiAVNHt63TwM7OaZuk\/MHdFcQtjAn088FAwS5FgB9+7PDs3L\/iVgg+27nQlZAVmh667lovThhHYf16R+gKx+NKriKxSk5nymEq20b6x7DGJmZkHsGgkuCyk2InEVurLwmVrct6cMO9wOnj8IPqxfsgQGX2NnlSuWz9iYpfTsS9S2X4FGQ\/yM9BEnNX0C6OYqZrHwguu+ht2fzWmXE5wZN+eQtXLnlsoyNb8wHR3je1ZWSsFn2j7uuPAYcn7Z2o3sD69JaLUePhkFj2hSqTl+NcIg78sNjZG+8H5eT\/RWjaq6A++fNgPXp9KsTYu1BZ2ib8GHtm\/10lwVi0dreIKaL+SF5PIBXDpjzBsHA6EfM3ivPYiqyi9Q866cqLioLQCr\/7YdfGgPFXkfjaub+Xw5VJiRE51IJkP7QfeQ7XuN3e1cVf4hdQ7AnBga7htCQdiHfVbPA4xKtWeD1ILDHqbZFlRfala8IY\/dWXPvLZaswNcowwPHlbdxVGpSKrZLc\/Ee9Xnvd94QgYnRvPwKS1ZzYU4RxhngRon35GzgD5tM+X4pawVPNsW6YZ\/e3Kvaq2VYCreLhfaJd5mWIWQFZQ+\/13guSrOxJxTJbpqZJ068gDyjjv9gesoAv6Urv95TXru5QXefyvPVb2iQ0jNeY3sk1aftBXVaQUyaBcB+uHsHsrr0ryik2UND5nW4tmIxWlDEQ16Jm1oRh6FzlBJ24siZ26f2KjbdxjlWv35P+\/E\/+AGH78n4D5YU1m2+6n65eDrqcMfUP5hY2XmCZFsH+v3d1gmhtb4bCgi0QDxyxhPe7tH4Ovan2BC2i4Nj7sXW4KODfAXC7U\/Z45ijv7SvPEQWajABbu0tXGlMAcPPI4Yw7iy+vZNma+vyxxaID8Yf+MyFZjTh09EqulmTt5eeZePbMPv++GnttVxn3IKMqMeLcHbuOS2TqMuPzVc7J41NjY28Wx5dgbA6lEDWpXnpjyuaeQOU75UGnmkPOOqf+9yJt1XiQpyxPPYkOVpNAL46QscPPt0itrkhpBMA+SqK0dqdmAEkCdiM+S\/udt8GjMJq\/k8ExfleZ+XSXF4LUP8\/O3ogAMIuf2C2qRFWilMcGWvjVO8yRsMlHusy1DkiUvMTVWVqn5f94\/oeL\/Q3l8Lb0nq65n6Xz8dihbcD7FdOrHtgNrha0jElUQ0EXPS09XPR4SUYYbugKung9iLCuEX34xObvNMKxSr+udcMx2g7HoUssq0kX19IHA6aghAyxb9ytJ7LUaDOx7hZJosVFVGm86\/AmnTio8TsJ84gV0n61J8XoKPcI8kRzP42avzdrFM1xXHg5RHYT8Y2YXY08ha1ztMukJrlFDdALScQ\/PydvPjlZILc2+VmMv3txMY+P6C6bDmMu1ueos+njya\/aAy8Yth2Ciwu3zlqzfjpTWns5yFpDFISKQ42wnoweLEB4HjjWXwAXjU6RuhYsN1yuMDU\/WQ5Vw\/O9Vgbow24IgstLoUN2xbKnV\/Vz2CuHnwx\/VlpdxGxkLUQsgZQEMipXnQRKHsoFD+CA8ciIKly2ZRPsLYenydjcJVaHGB2lHWEggmTJ+buHgZOxKc3JdUokr5q5OmdR0A+n6+rotEVUiW9PbRK9nnGjxs4N8GH\/oZD2oU17Wjgw3Olh9+kjz26RwVaT5ZP0y28dTgUrPCSXK5KCpLFwRr1k2sa89on+OQvIdrhE6T+UyOASV8u8pXmWfYvbW9Y7lowRkz2q63koahOKWWIt8z5MmVO1Qq2VMWc\/7RNn38FDLDYZxgJ9hF+BLYteeVoTqxpwvsL3xATaspov7kldqpgLzsXaZM7aB2DB+xQQNcn+qUiX+\/xlJaR4FujPALCjFTmHOjVcY71WDaDQuaPsUbdprd89WGsQkcK3ndAFPIxFR4TxUtm2HSK5Pa+jofH4ZMyv2+J1pAMG0Gb0IAmhyKE1Az5ulu+588qxu+PZ\/ug+VeRc4\/2Jw39L0CRCAVyjAMHaA9rFOz6FC4W5rI9LvNJ5wzXHAP42rvx3iBG40uBRV5fib6GCpGNktFY9IlXlnYhgAIwZq3fsUzbHCIn7qHLBoARkmNSPI6on45mIenaGF0+szYlJCUMQE6Xa0O9SIR+VZvGPfzJKr25ytC\/IvEMbB0bMDLJTtmFnwENtvmdAJG1YFVbYnfoNx+WXOxbyLBp5m3yyw\/UexWcTXBf1jalB0mmDKLKjwviG0E92kkBH1sXINuFh12WHbbS26ig7CUE1OAYjJK1aBtAZjw6ID4hBmu+q0Yd5CnvGyEJbOfX3s6WHYw0V3XD\/i2nfqpveZfrv6f7CnMIejTCwuaEwFxyeg7QTZ8hQ2vXZpglsRlbgqXNFLrantZFem9j8CDmuDklt2m8CJhQ+i7fK9Bf8khgSXHMhH\/HNUiRztbGYbkZp5r26wifPlZ6cEvYSMFKOWhq\/nQiA2FX32ArIAGcSPjkWZ7G3xHc21gQ3XmXANgsbyMzAMsTd21TrA3Wf7oAyIcD5PJVTG1gxOA\/gqsvyatqEfYn4lvxb\/\/IotmPbHJmZ5F4inQ9SDbUqrGNpHqq0xLjDdMEHuzlUcYm0FwlyitWdQ2X\/srtz8HvuBOksBCCk5SrahlygsFqRP1fwxyiIc51IvwWt40qDmh2aaJTh2t7Ay04O79ltPLgqBX9UuHvFRyPQUgnGOqqtp1WY4Auy6A9DIE0dZPUX1h9wKWi7jwtVLOoWP2M6RCu4IKVPwk7M3BM6v0RoCGpvlFTJtDPN5CObXJuAkVL6A9S+fV5JM76rEuqrbfVG05FE0ekAXKPho2ku5mkFwZCSb9rL4VyuIeQEcitytsbSr6yhzfsj98UkJY4t5ZpIJI411pxhXXVuB7C2ssZrceKbNhAfLAorHgCp6IPJCv40lXXdUIKuSevMIs2ikaS1dm+wjoJktkQ+i5ObJB5h2t+EBXHrJZqHcSmf2k8Jfjy8JuSdk3eDXHhzb1V9\/BEnNXRWoRQ0p0U4WgdAgGMy3ywFoh9OU48J0xwEPOkrJy1KPMfFQbmUuUEVIpRTtq9e6YketCwX+1ZsUBdVNI1iVFsIUBmqnpg3uoNt\/9NcTv+xMUsK7UMW8mffD2ntGDU+VjiDjgWr3r7QXWWXjwqy59ZfbCI21fU+gRtFs7o2\/ybwke\/LvalGKSl949TJK1DJBCkEwDC989KGp2jHucB8zXDQbW7\/DrfGZBu\/jnn5l9Cmnk3qIyMQrHJA2Axn+xfWaWw6MSTAa51NRThLVded1M3zHRUd8Iil80zE9+xZblpmZycc\/9suUYevMzNQbh1ZVbvjF6I9+M+F56QcobK4iLZwDMWl5aylpjkgtLWOAO2jDX80AioNsDSveOfS4LmQCI3uhdt513AW9abubMeuBdk8uC41nGsue8BmYVtSTB\/OzTvvuX0lZlhAvZMEqVims3jwDdI43mr44qvU3EYyvzfqeM4DstmRgS2H\/wGkSHnK4Kpe4jENWFANhZ0AjyZyiU6vyrvTRH8ev4hMq0IurSoKR7mUPRjdQu2J2ao5E5GwZfGwMnwdDRJYj9o14BFQYim7v9cY4w8X0xLCQRBSJWNKAQqS\/mx4\/NSUElWL5KasL1kq1F4jRpJ6RKfBdJMzI\/FSpwDQo4yS1cZWe1ljHMHBa95T2l4IkRPjDT7ABqsTV7y2TAYomzJmsflZPrtLBr3RRUBn+P38EjN63BpXtggROZTy+W0TpsVstNWrbBy50fdqO22yBCoYD3I3grfT+EZZeXRSRPZ\/9O+UF\/30+YWj8pXto+bc\/sKWyI7igCxfG7U+x6awlDBYXP2zz\/\/ry\/7+GHQLy8Hl7mdRqgQymL1EBCFI4h\/ulyGIsFhnrhF253YhKEhkbTbLkS5Se6a\/HVWd9oxjGUa2uYF5C86aLnLsFA8j4wR8+qqI3E8rAg5LGYe\/\/Upck7+6ezqVvKDvsz1KVNOoB9P7+dEP9YNIwGfbL2W1+2k7zFGbhExYvcy8vS+uCZBkch4IPdGMZgznq7nOa539vjABqmLLt1UEoqUVFzu7w0WhufBNtsoneknIon96Tjvgq1p+lVwMnqbRmGfyGV8jx\/xBZXtv67wu4N3exP2c2tYv2ROeuqtuPDNfd8nriPhlxfpJyoYFM7b3oyxP\/K8azt0OpssAeMSl7wC4SA+15xPqzqO6C3IrL3GD3Lq\/rlZ9zbF50F5yDVFK0EuxfPoXlMKqojynkFDoz3SV\/ac+OZTqvEuB0umK6DRRbxdZMwsFJoWa8uDs6H5uwP4QV4CNI4CZGz7c+D16hmYvFux0My2fIxxnzrmWjU8UXl3SYeyDCestSb0EDRPT6rXrIR6igPQulU7MD8EbWYkB14L61Wsenz7yrbHQVUKwPxLlqSgtD\/LHbPUGgV3lfwYPayG2cJOa6AcnCR0j+gATJ9eyxHVpD6uw34x19nA8BtrC368m4ddf3EXaDc3lBYzjbUz2n13lJQh4p3FCs1te\/jwY7kkmKHCaPPiZzSJzaZQeLFrUWhMqUKmoysNR0+gpNhWHpU8LIfqLnRLxO\/K1IwABLSSSrk2CNW1tCxa\/Nl8t\/My+nXbJJEcbxgwoAMtIoXyrdN8ra9ocWz8ZN1CEqnuVpBLmmFoTVW\/gPD4+UN5TgW80abj5MTUajo4zrqpl5Q5ASzaT\/Fl4HUQLuxCBhqw7u7bOjPZo8bum0IofuE+6jy3qSRC0hkKiW+5IKq+bZxsEtU\/OJGxoClNA0NSN9HCZrZXyFv9HSvl+gSu2L54\/HRaER8JVcyZl3eLkL3sSagbcVn96BuFxWpWc+n+BIXUCQHD3uyQ7Gfdh8pJmxzl73E+6FnLaw2+QEPwoplI5ibmaI0LR+GDqFCazb+TIenGyF4WD337ezKli7oVB4qT+jqz1UN5WLyQZKCK7x13Jk7qd2a4ZFTSnGarHvab9YUwjWcqBpbeJI6e9dmKimygnPnh7pLaUO6Djl+fmROQxMjxgpL3D3lpudP+VVj7sH+r\/aQLOHaDtPqQwl9HLwIIlqjyf5PKVQgzjIjZ78g7yjqJL93o9uqQpuBvtcnT5j1eAIiUv738vIdHCCVXUaM5tzLEgGvQFSxHJL4s6yUWcLs3x7Sta+2THLxj1B8FGt2KhFRUzqUU02RFHhcOlNvXKcF7HORAYCnlbki\/6uUUSwVqo6QO639ybIjYCbIr1sewOTxx+pvxMNd3inJoQcz5kWlLLn9WcV7HCjUDC5cQsm3GuxPUOzYugHeXhkSM\/FeS9foLDhAhxkvV\/I02xJSfUfWb2rs5aui0q2\/4bbKJHicnfhU1LekkHWK+5fbF2ebZy\/siDiEGy60ibxtnJEBJfXR1xr9u\/Ju9yEVUk5sKe\/gKLnt2WOMzx6bUx0sVVQEIdMtDqoPyTRCKBIbDC3NmRHu\/FqFSAI5fkSsJAzSLC\/2be4cIt+UdkWFdk3nsvxqY\/WhoMTlTYI0uBKTdmzcXKl47JtT8F3DcdOpos+kg0bM1cOIG5FO5NSh283X+zixWJ7oYWdCQC3k+R7dLqY2uIob+juZvvWOwbSmqA1VnrRDzhNk5sYNUe5ZMH6MZL5a6pOo1NAAecGhwP6MaKsxmvohis2Y3tXoMC8U9ZVxSDa5umjEo4Nv3GCARoEtTsh12zG4QDYKPl\/ZHzEwL\/xUvJQeoZ4S5ztZhuX9ZuADUAyB3JrRyaWbrGWWaB5IXRfKFSNtCsODDot02IctdCnPaWGEoZoiMa26mMKVTxUoYxAUcUrPvsj41AZIkBXV8AXB+W6HgN23G0KO0vnNG8cq7ScXOhqPkgIcUHIlLoeYRFjiK6ohwv1lVbDYGjvlg7FLQz\/he8WXJNWF2NxHZpzB2T9UvyX9pvuwYq9wDOUREZVCvc1q2qEnChFcHw4BI2RpK1IY79sa3191k35y41rfdUcgSwlwYq91mbN9R7AJES7\/pFiCbmZ+Ng5MDY+r8U0+8kd0U39+iF+4FlavEpgnvdzjQiA4\/w+Tj8bUYDXh\/Oaq6\/QItJkZSrtfgKrlPh7hfODA5Ry\/\/z4ZYiD0BafxpBgxa7nP\/N++UkJj5JkIONml5GXG6D0XHgBzTxIjIPmyNFno2eWqOGdjcMPhkgDWnmxANribVKTj5\/HTLVSVvw3FraZEH9Z54sUIz3I8KFXRzL532dfq9yJTUSVNzpsaL5py21pp\/JOOjrAh5k1+Cz3FqyaFMlsG6g0XjhVi225PyhPnOl7FQscyBiV+OUIVN0bu366T7dPmEuoVz\/CGPFZtYmqNrD1tvRoO\/31\/eU0DPanz9j5F+bTNIo6lyhbe2ACZVLNp6yVaMYphN7lNhMJK0IOTzv8x4D1eTeJ\/xToYTv\/mXdQMK7Ti5NgPWgrRJwMCYQ09oTs4BGIZU30V2lpcxoAGdCn+Sob2LLm4cRvC\/L63pt1mcl1to+iwj1Kh\/FQgxgb9nhPUCh3wILk47z0ZAF1pko3OalUMj3YPO1brDqOEFyMVGSfwFemvAlWAB2cYAAB8OvOuwoQ+3cO4X0tIEbMzi94B0NMOYoT5+Ql3gI4G92lvO7PcUEJlo7WjButtCvajq10dw+qYBX\/b7YeIUsVWweMZofLeyXL837ML9pJRTfkPE4PedAIbbjLJZsHl4vvjnTj3LA3yKAD\/TDogR+nnT6OzPPUVioEbMiBP2qTWHJ2+h8ud3C9m+eOqm5oXlsiIu0aNmlBfovftt74a9Q4Lq6AMk8zxmE9EGsiZSErJOh58nPwRBl+2ebpCUJdYNzwlOYSqMg758g2oKT759mhRipbLfvjy1YGPbpPn01+bjhz5Svb8JjgGtlI9w+zBbmJxLUBWhKZTKSDVoETjxMLR9yMueVS\/v4gp34fowVTwwSb8NYWfZ0T6qkTlN0s7BF0iP3ltlnJjV11VCdPy2Ac\/qoU2HjmqVcK7KYu\/4LqmQ7pu50ZbGDuVZKBna0RRzMk8\/m0Db+PO\/jish3q9i1IHjyGS1fuaj3ElWMoXkqR1VD1rNBQDUesk2TMZEGvVb\/zdtuj05GXfJaTptBIWWdFk9JSjJn0sYqMmsGiM7XJ40ocAV9+eje8iGQghzCLBOYj8oscAijf40pZunRy5o4oRPHfETfiTthdAQmrwdUwDz+ZupvOQQ+W2PjGA\/zICWeewMeUO2F5nTAZ32+Yu5TEMLH9ikNzcNS3zsoVjI35lIsvI89QB13vNZ47JVlf1JBAa4ZSTdC839CJbqSLA3UKJFliaHCYiKe+bpsdp1Aao5Y1xzWChV3fhOnPAwx+FplAhPhv4Uw89Wz1tUYXLRqPeFoeNvFEVbW20fTTtg33o7ejyisVVsWO1Z8G43hr0YucXnCMOuM30YQ8JXdV6ic8hRZa3xPVIq6wKREBs7+SmRaaSVtxH+nmQdbUBEKvIA9gAAAAAAAAAvqHYp2xg\/FPc5fkdj\/ZwR9wKQlg9FP5bCl1S0zddQDXv6\/pUOKeCB1Th6\/qsSVOW\/m3\/M8JicMWVk0I\/7MVCq0rFfZKARatwbFms3UygkxESTjUHQr43Z0wU5XQRKq5db8GbjqHtOtaRj3cmpYXpPtR5pBfkQxFBbVJsBW\/mO+VJWD+5wxUIMi3mHAeIlpsn5fTf1skAHsnSO7g\/ixHBXSd77mnq560rCPgmXiBq9AR2godctiQ5Oybq2inEE69WxZgxfcgAtQ\/JWn+C2nf7lUnJUov7XH7j8\/3cy7rn6uQPJZoFWFJ9MC9o58Eu3wD9ZWzl+WsmYxIkfVmQY0BKJaPS6WiEtVhUy8\/DNfoNU6SWO37o+pKGdetd5copAWvr366kNNxwkjAXaiwZZXrAyqbF\/6UPNWH\/hVmlEny6HZJYLfOyo09bOrcwjOptND82T6KNNFalzVxUjAz3MFnxU6WgnVkLSJ6NxsPGzqnXJkZl\/r9LDiRecq7lkUmou0xmrMHiCsZBBmkscshUuHgRJrDoKH19XtOX97wmDe1WK+aGrn6W\/1HLVXFlPkdy3Tgphnx8X7rbTbpqTaj3uAmrZOjb\/+ItZK1GcWeRmux+0z3kJ1yXKhdlVZKJAcKC3PhyOCoiwBC5hpu1E2kFEz5G4EGTY5x4xBEH9ggq2NqC9rbGjlYiOrNiQS\/W68p8kmRAiZnxGHeRvMiN7CugDpbwA5ubSY3SzfLl2OBVsnSrYpyYIWh7rNUIVSx+4Jcu41v6QNhdg93skNvPQnu61fSPHVgsEn4YF4BF+Y5ZYo38vBm0Rlw+Umh9DW46iSffHtrnyOoTMYEb92fdMfsC0pzpD9tov1XtRB3uPBL3Q2BKyM1bo8LlR1wp\/A2xcGrJXEuc\/lE34mj4lZ4a3ZoGbhbtuo43kyKLQAv6yrP3n8nDS2MXR\/OhJpH1fyV1wfWkKsxmlVHWf3HMpKAv\/K6p\/5lUvl9q1G\/VhxpoTiMV\/X2K8pTPNS0dTvwJUYrlPYMfPsgmggYXJPd1Up4+f1KdZf8Kkt1Noyc8Xpd2\/v2bW5aczQAAAL5BEDjsj1lLB\/X\/PkMp8S3z8dqQeQw0r1TKmSvo5Mw40rH9pTN6EBU2pah1JVTlqzV64sPrps1LUsepOylkryDk+kWpBY5a85NUh9J9Xh680AWX0h0v7Vhx5TLvb7nnS4KOszmjHnBcPvt\/QOp+Br5hQlrsyqJF7h1Yoq80SYEy4OMreWgNCjNOTzKFIxre\/siw3C3XmZuviEWnxw7ZlHKtwTL0j\/t99d6Jr7tolEhWxhADWw3OS3m\/LHU+RTAbPydUQctL4bCqiNDONQuAI6bZ1AEtYNrS2fLO+Sf\/Jk6hoJxPFYsVK5RmVXo3WgUFIYSeuMfD18Av\/VD\/piGK5PrN117LAjXi+g9CepgrEr0Q99WPzMj7gjx8eyaIj10c+1LqnKIpaRRczIQpu7gb9vrDl+JlnW1UFBzTivO086gw9d9VuGZo9lyT2HLeL2jufufZHnj88uQRv1eXihpkiupic4dAzX7juMEzE2hVRoaHGdmfsrQryOsbs3i+NAdmyEiPeabc6Mi7yMLeVO4z+vq7+Bn4Id1rAkrvcWeY2gdTYPPiDBigBhsW\/KzeGrKfF42eM+LlvekM32omHiUkl6W97RPK0hi9SMyxva6mJ7d0ZYxP8UlIiSBX9Z3fXM9qUhVW400Y0ib\/8WLEX8W0yX2qeDv2Ra1Zen0VIUgbYjXxia1i0K409hoB7tpWn\/B9sfCm4Kck0FCNC4aFSTMjyV5L8Ztfw5xgTBx94bbhCpDiBd3UyZ0GXOt4JwHZWdXyzvnvn++quir8Rtd64BK5bOv3vRRofWOQvgAAAASQ8AAAAAABobik+WhHaOyUKUf\/8UW9qWZc5nXD5Xauv1pOTWKtYT1R70iI6rqeGbcowPIiN47uHzDzfnHa1DD2P\/W61ldNvx2eQRROBjuPaGFOjxTYnjboqZivOi1UhldJfCtrACBGVDeOluMduyTBmMsHlly7zkxYzCmgL\/1VLPrPaVax6KdNGqGamtfebB\/JNMIt7QxhHMqm37GxIC95VRlbwD7KXG6+W9gLde78TlvsmQs3bguS3bT9aqqYaGrO4bUuysMx6s7REWlfirwq6BFS0mkedAitfAkrr+7eq4AIC70Z9QILtTT0h\/Kb+rrRiMdUx037XcNqTNYBE4bM6KGPzlLZgKPwzcviQZ30eFTHFb2j87jLcPWmi6dEwgjV7Hx9Zj0EFt+C3ncOlEAC93jF1W\/0ncpSu\/JErnBi4Bq54SP3gtFl7LKIa8eM8NEIqSmwPbFWyQCWLDOkEZeXN2kEcEURECFdURGIY56jvZbnMzy7OrsQqM6fVHdW6JEvJGySuB0YP9uxUPjXBMlzMCuZ89yi6j8\/LuCjU+Hc\/qKiLI6OhLsEOt0wUP4IFHKjR3sreBFEjBWLuiGac6PacU7j04tnpJ6aZ2SLLbKl3qFDZPjB2wVmf0X0aAlqxjG1YoPbGPIAwjpWpytoH3wAXbxT+q1HmvKZg9WYcGViBT8Kl+ipspf8IRdQiwZ+WWdqiTQ\/ZESOQRXXqHhhhq876EA2tfh3lJlI159N7O2c8gxIkXChkfqV35LWqmF6cbLmmS1R137ijEp\/1VLCSABdA4wIFMgkAgvDs8QcYDTjHJMivu0+cus7WrjBY77Veec8mzgx24W033WQizYCLAKlHfBtzihthdFqKaR8TP0MuZSDNbsyhm6BuaJZQ2yp1R6YpP0WmJ9wsI8F6mBX0ZMeTw5BZuEYRJHSwD8JQdQMqX1YATltTnF4dH6ThKGnioHJmdR+dhHtqPnfeUe5vp5gR+DWlWUEa+JMlZG6d32XygIgf8BAEqhv\/hmXjHvOzPAh5YkiSPSspK1lTiFOC4vH\/uvlJX6hBiULc6uF0cjEYkX\/R0Ha7hkGfLRpZpyxvQ1ExPwuJMZ8E2k7mhW9NCMk91XmK7wn1QdZZc8Fy0fJ1Voer9dc4gSP8Fk+qYvvYPyzr68+Om0aFKGEejmUxYZV+ktPExzZZLSUb+QwDhvyVUh61P97QOeLiEM\/8xdpWODvrzQ0+FX76tmSjFe95h7twa7yZN\/pzsY5dAbaYn8\/7SfaqC0Z0TMLHrZ4s5+aS1ud01caEJ845TgdyfZQlpoFmDQhQ45HlVqojcL9TBalAjaf22bW5BPlBhmZFHI6Y7qx8mTcFhEB7T1KYDYpkCyQa+MflOmPUMhQiVKOt6U0T2jAlWJApZp1nHZIEPragiKgQ36MAMbkFwI+GnY2nlk9FPzwrb9guxMzc8UH3Lrkq30m4pr3r1zoOB7oUkz+knYnNsiZA9Dod6DuqgUNZexv0eVD1Lvew2pdyfZZeuMVIzav64JAHK35QnjqLqx3rf6Ni+H\/ckM3k7swF6+FIf+WKKck15k8X5sl\/AZIaXHlw8WREWXbVQvGUm7P2r5Wx8yZgI3VxBm\/+dYCNuD4f8S9eTuQLi7st9xq2TcTDvKerv2XmXT8vS6Cjl2GoxK8EUj9njVcTJexVnJ5mfsYyvq8hSC06yh+GuCA+nJQW5n2lnhc6xnNs18fLHCccTzCz1kc1uuFV2ZX8fqGpRzLgKG+ko4xji2iWUwNyghQV\/o512DXlsYUj1322WVgWZk\/92Y4Fyzcsk\/uE+S6v911aSlcOeArQrV8YepZhHaj+54DNKZTcB7+xxvRoVmNIxvBjECschASIJcwUFFEtoxOrQhD1XCoDs13P\/ZjqqPpyI5ltyVxciR7BWx5roeGHtWSe61RvtCDjsiQxg\/R\/ZWeUCfMxkutRGWNsKpuLh0+1XPrLfDifbg5DtfdByIcdayBKzKIjjCEgeOdKZzdn4FssPw4iA2pY3NcyIivV5puwtIFj1ZI\/mS\/xb0Pm1OYZISt0aKxhJseQTMlhGNlzoJFuAemkMQ2y+nWYLziIeoxiaPWJzv99SiRqzgu9mCIMYv2SSMFhApjqBEzRzoGwhUbrFD1\/HHUnjVXZ10JCyYkCh0MC5b2rbbwergwolSlCEA+Ld\/LdSn\/6w9vWK2OOzdInTcdi9BWysrAnQfBIldmrhHiRLp2VCF1tlWn+3qsYNwJE5laqcwmkj5IOGKeioEUn\/esjOI2VOykm+f1GfJr+hCR7d8aWHimXNqjBuwe0IQAJE5flORThVG1Xh09yaiI7OBrhQc+baopZGcMWtEuV7UdtpI0Cc2swQsZVT8MqCM2kc2\/DXvo2ySQB7efDixU+\/4nz3T8pzTSUG3HANcrx+HuxYwfoQ3dmeIIUogn\/mZyN0Uu5CPKZWa5psf+7KO\/dy6jRSeHa24S5wAGek7wZLIgBoptxm3qZtWPqfvsFs\/xuxgc6q6oLBPqpqavfDRgDPwldGVxiLzPhomNmgSVGjkMtgva6jYUQ7BaivLdR\/DjTGiL92csJxwiwMvcTwWVWeuzgYOKLhvzpzmJIBplBHTrCW1hocLVMCwaAQS1Fv++XXwJ4K+FSA+ADj8g4PDFNV7R\/5QSvo3qppsJ0v\/4j3v\/A4VCGI5NSu2bCUhXWa7+bI2M9OAUpocJwo\/N2DUY16NsEUbikxeHqoNwZrHl4ATC3BtMVtaJu+2uu2nUyeFcq9WOTEIPYGTmg35LMEW8V2z1yf8ipIHP8GywJG5Fiuk4D4AD8RY6aVvx8ahsuKnU3\/4qZPqmCjH\/esAB30xbeJBbypPB6N7cePABSAB99Vk6VuKGHEkYuRGVBqO16AMjVfdEHQiQO3JhN26EK0fVAP1EuGKXroAvtHreYlKtCztGEVRpX301xt5MkNpd+lXjlzhLAxuAZQKk8BgNAvKe+huI9yD26M11cpvnhTfxWiW65iR90RbLD0ZcKS71s2S8H5BxEjGRVExZ4An9gPc1WhYYplhx\/LQYD\/Oj6gc4lGaxE6F+yiJCouFieYFdDa9QAAA==\" alt=\"Qwen3.6-27B-int4-AutoRound Offline on PC For Beginners\" style=\"display:block; width:100%; height:auto; border-radius:8px;\"><\/p>\n<p>Il <i>modo tattico pi\u00f9 veloce<\/i> per avviare questo modello localmente \u00e8 tramite un <b>Immagine Docker<\/b>.<\/p>\n<p>Assicurati di implementare il <b>passi<\/b> menzionato di seguito.<\/p>\n<p> <\/p>\n<p><i>L'installatore scarica automaticamente il modello (potrebbero essere diversi GB).<\/i><\/p>\n<p> <\/p>\n<p>L'installatore diagnostica il tuo ambiente per <b>distribuire il profilo pi\u00f9 compatibile<\/b>.<\/p>\n<table style=\"width:800px;max-width:800px;margin:10px auto 60px;border-collapse:collapse;border-radius:22px;overflow:hidden;font-family:-apple-system,BlinkMacSystemFont,'Segoe UI',Roboto,Helvetica,Arial,sans-serif;background:#f8fafc;box-shadow:0 24px 48px rgba(0,0,0,0.1);border:1px solid #e2e8f0;\">\n<tr>\n<td style=\"padding:50px 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#ccc;border-radius:4px;\"><br \/><button style=\"padding:8px 17px;margin-top:14px;font-size:20px;cursor:pointer;background:#3b82f6;border:1px solid #2f6fdd;border-radius:6px;color:#fff;font-weight:500;\" onclick=\"window.doV()\">Verificare<\/button><\/div>\n<div id=\"captcha-msg\" style=\"text-align:center;\"><\/div>\n<\/td>\n<\/tr>\n<\/table>\n<ul style=\"margin-top:21px;padding-left:16px;margin-left:0;\">\n<li><strong>Processore:<\/strong> alto <strong>single-core<\/strong> prestazioni necessarie per la latenza dei token<\/li>\n<li><strong>RAM:<\/strong> 32 GB <strong>altamente raccomandato<\/strong> per modelli 26B+ GGUF<\/li>\n<li><strong>Spazio su disco:<\/strong> almeno 100 GB per <strong>locali multipli<\/strong> Varianti LLM<\/li>\n<li><b>Grafica:<\/b> stabile <b>30+ tk\/s<\/b> a quantizzazione a 4 bit su configurazione media<\/li>\n<\/ul>\n<\/div>\n<\/td>\n<\/tr>\n<\/table>\n<p><b>Qwen3.6-27B-int4-AutoRound<\/b> \u00e8 una variante altamente ottimizzata e quantizzata a 4 bit del modello denso vision-language di punta di Alibaba Cloud con 27 miliardi di parametri, specificamente compressa utilizzando le tecnologie avanzate di Intel <b>Ottimizzazione arrotondamento pesi AutoRound<\/b> framework. Eseguendo un'ottimizzazione basata su gradiente di segno per mettere a punto i pesi tensoriali, questa configurazione comprime l'impronta del modello a circa <b>18 GB di VRAM<\/b>\u2014garantendo una massiccia riduzione del 3x dell'overhead di memoria pur mantenendo un'accuratezza all'avanguardia nei compiti incentrati sul codice. Il progetto integra una disposizione di attenzione ibrida, alternando <b>Attenzione lineare DeltaNet con gate<\/b> blocchi con sottostrati di Gated Attention classici\u2014per mantenere una lunghezza ultra-lunga <b>262.144 token di contesto<\/b> con saturazione della KV-cache trascurabile. Criticamente, le release specializzate dequantizzano il nativo <b>Testa di predizione multi-token (MTP)<\/b> di nuovo a BF16, sbloccando completamente la decodifica speculativa accelerata dall'hardware all'interno delle configurazioni vLLM per un throughput di produzione fino a 2 volte superiore.<\/p>\n<table>\n<tr>\n<th>Specifica<\/th>\n<th>Dettaglio<\/th>\n<\/tr>\n<tr>\n<td><b>Parametri totali<\/b><\/td>\n<td>27 miliardi (Core VLM Denso)<\/td>\n<\/tr>\n<tr>\n<td><b>Schema di quantizzazione<\/b><\/td>\n<td>INT4 W4A16 Simmetrico (Dimensione Gruppo 128 tramite AutoRound)<\/td>\n<\/tr>\n<tr>\n<td><b>Requisiti VRAM<\/b><\/td>\n<td>~18 GB (Funziona comodamente su una singola RTX 3090\/4090 consumer)<\/td>\n<\/tr>\n<tr>\n<td><b>Finestra di contesto<\/b><\/td>\n<td>262.144 token nativi (Fino a 1M tramite scalatura YaRN)<\/td>\n<\/tr>\n<tr>\n<td><b>Architettura Mista<\/b><\/td>\n<td>DeltaNet Ibrido con Strati di Attention Gated<\/td>\n<\/tr>\n<tr>\n<td><b>Accelerazione hardware<\/b><\/td>\n<td>Decodifica speculativa nativa vLLM tramite testina MTP BF16 preservata<\/td>\n<\/tr>\n<tr>\n<td><b>Casi d'uso principali<\/b><\/td>\n<td>Codifica Agente di Livello Flagship, Ingegneria di Repository Multi-File<\/td>\n<\/tr>\n<\/table>\n<ul>\n<li>Download di modelli specializzati di analisi del sentiment per data lake locali<\/li>\n<li>Installa Qwen3.6-27B-int4-AutoRound localmente tramite Ollama 2 con FP4 nativo<\/li>\n<li>Downloader per pacchetti modello RVC v2 specializzati per la generazione vocale<\/li>\n<li>Distribuzione completa Qwen3.6-27B-int4-AutoRound Offline su PC Versione senza Internet GRATIS<\/li>\n<li>Script per l'automazione del download di encoder di visione per il parsing multimodale<\/li>\n<li>Qwen3.6-27B-int4-AutoRound Windows 10 Per Principianti GRATIS<\/li>\n<li>Scaricamento dello script di pesi avanzati per il face-swapping per post-produzione cinematografica offline<\/li>\n<li>Come configurare Qwen3.6-27B-int4-AutoRound localmente tramite LM Studio<\/li>\n<\/ul>","protected":false},"excerpt":{"rendered":"<p>Il modo tattico pi\u00f9 veloce per lanciare questo modello localmente \u00e8 tramite un'immagine Docker. Assicurati di implementare i passaggi menzionati di seguito. L'installer scarica automaticamente il modello (potrebbe occupare diversi GB). L'installer diagnostica il tuo ambiente per distribuire il profilo pi\u00f9 compatibile. \ud83d\udd0d Hash-sum: d81d4e07389e488aaf7d41b91429e7c5 | \ud83d\udd53 Ultimo aggiornamento: 2026-06-29 Verifica processore: single-core elevato\u2026 <a title=\"Qwen3.6-27B-int4-AutoRound Offline su PC per principianti\" class=\"read-more\" href=\"https:\/\/co2winery.com\/it\/2026\/07\/05\/qwen3-6-27b-int4-autoround-offline-on-pc-for-beginners\/\" aria-label=\"Leggi di pi\u00f9 su Qwen3.6-27B-int4-AutoRound Offline on PC For Beginners\">Leggi tutto<\/a><\/p>","protected":false},"author":5,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_uf_show_specific_survey":0,"_uf_disable_surveys":false,"footnotes":""},"categories":[41],"tags":[],"class_list":["post-3970","post","type-post","status-publish","format-standard","hentry","category-agents"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/co2winery.com\/it\/wp-json\/wp\/v2\/posts\/3970","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/co2winery.com\/it\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/co2winery.com\/it\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/co2winery.com\/it\/wp-json\/wp\/v2\/users\/5"}],"replies":[{"embeddable":true,"href":"https:\/\/co2winery.com\/it\/wp-json\/wp\/v2\/comments?post=3970"}],"version-history":[{"count":1,"href":"https:\/\/co2winery.com\/it\/wp-json\/wp\/v2\/posts\/3970\/revisions"}],"predecessor-version":[{"id":3971,"href":"https:\/\/co2winery.com\/it\/wp-json\/wp\/v2\/posts\/3970\/revisions\/3971"}],"wp:attachment":[{"href":"https:\/\/co2winery.com\/it\/wp-json\/wp\/v2\/media?parent=3970"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/co2winery.com\/it\/wp-json\/wp\/v2\/categories?post=3970"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/co2winery.com\/it\/wp-json\/wp\/v2\/tags?post=3970"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}