license, language, pipeline_tag, datasets, inference, widget

license	language	pipeline_tag	datasets	inference	widget
apache-2.0	en	text-generation	Skylion007/openwebtext Locutusque/TM-DATA	parameters do_sample temperature top_p top_k max_new_tokens repetition_penalty true 0.7 0.2 14 250 1.16	text TITLE: Dirichlet density QUESTION [5 upvotes]: How to solve the following exercise: Let $q$ be prime. Show that the set of primes p for which $p \equiv 1\pmod q$ and $2^{(p-1)/q} \equiv 1 \pmod p$ has Dirichlet density $\dfrac{1}{q(q-1)}$. I want to show that $X^q-2$ (mod $p$) has a solution and $q$ divides $p-1$ , these two conditions are simultaneonusly satisfied iff p splits completely in $\Bbb{Q}(\zeta_q,2^{\frac{1}{q}})$. $\zeta_q $ is primitive $q^{th}$ root of unity. If this is proved the I can conclude the result by Chebotarev density theorem. REPLY [2 votes]: text An emerging clinical approach to treat substance abuse disorders involves a form of cognitive-behavioral therapy whereby addicts learn to reduce their reactivity to drug-paired stimuli through cue-exposure or extinction training. It is, however, text \begin{document} \begin{frontmatter} \author{Mahouton Norbert Hounkonnou\corref{cor1}${}^1$} \cortext[cor1]{norbert.hounkonnou@cipma.uac.bj} \author{Sama Arjika\corref{cor2}${}^1$} \cortext[cor2]{rjksama2008@gmail.com} \author{ Won Sang Chung\corref{cor3}${}^2$ } \cortext[cor3]{mimip4444@hanmail.net} \title{\bf New families of $q$ and $(q;p)-$Hermite polynomials } \address{${}^1$International Chair of Mathematical Physics and Applications \ (ICMPA-UNESCO Chair), University of Abomey-Calavi,\ 072 B. P.: 50 Cotonou, Republic of Benin,\ ${}^2$Department of Physics and Research Institute of Natural Science, \ College of Natural Science, \ Gyeongsang National University, Jinju 660-701, Korea } \begin{abstract} In this paper, we construct a new family of $q-$Hermite polynomials denoted by $H_n(x,s|q).$ Main properties and relations are established and

Training

This model was trained on two datasets, shown in this model page.

• Skylion007/openwebtext: 1,000,000 examples at a batch size of 32-4096 (1 epoch)
• Locutusque/TM-DATA: All examples at a batch size of 12288 (3 epochs) Training took approximately 500 GPU hours on a single Titan V.

Metrics

You can look at the training metrics here: https://wandb.ai/locutusque/TinyMistral-V2/runs/g0rvw6wc

🔥 This model performed excellently on TruthfulQA, outperforming models more than 720x its size. These models include: mistralai/Mixtral-8x7B-v0.1, tiiuae/falcon-180B, berkeley-nest/Starling-LM-7B-alpha, upstage/SOLAR-10.7B-v1.0, and more. 🔥