|
--- |
|
language: |
|
- en |
|
license: apache-2.0 |
|
datasets: |
|
- Skylion007/openwebtext |
|
- Locutusque/TM-DATA |
|
pipeline_tag: text-generation |
|
inference: |
|
parameters: |
|
do_sample: true |
|
temperature: 0.7 |
|
top_p: 0.2 |
|
top_k: 14 |
|
max_new_tokens: 250 |
|
repetition_penalty: 1.16 |
|
widget: |
|
- 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' |
|
model-index: |
|
- name: TinyMistral-248M-v2 |
|
results: |
|
- task: |
|
type: text-generation |
|
name: Text Generation |
|
dataset: |
|
name: AI2 Reasoning Challenge (25-Shot) |
|
type: ai2_arc |
|
config: ARC-Challenge |
|
split: test |
|
args: |
|
num_few_shot: 25 |
|
metrics: |
|
- type: acc_norm |
|
value: 21.25 |
|
name: normalized accuracy |
|
source: |
|
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/TinyMistral-248M-v2 |
|
name: Open LLM Leaderboard |
|
- task: |
|
type: text-generation |
|
name: Text Generation |
|
dataset: |
|
name: HellaSwag (10-Shot) |
|
type: hellaswag |
|
split: validation |
|
args: |
|
num_few_shot: 10 |
|
metrics: |
|
- type: acc_norm |
|
value: 26.56 |
|
name: normalized accuracy |
|
source: |
|
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/TinyMistral-248M-v2 |
|
name: Open LLM Leaderboard |
|
- task: |
|
type: text-generation |
|
name: Text Generation |
|
dataset: |
|
name: MMLU (5-Shot) |
|
type: cais/mmlu |
|
config: all |
|
split: test |
|
args: |
|
num_few_shot: 5 |
|
metrics: |
|
- type: acc |
|
value: 23.39 |
|
name: accuracy |
|
source: |
|
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/TinyMistral-248M-v2 |
|
name: Open LLM Leaderboard |
|
- task: |
|
type: text-generation |
|
name: Text Generation |
|
dataset: |
|
name: TruthfulQA (0-shot) |
|
type: truthful_qa |
|
config: multiple_choice |
|
split: validation |
|
args: |
|
num_few_shot: 0 |
|
metrics: |
|
- type: mc2 |
|
value: 49.6 |
|
source: |
|
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/TinyMistral-248M-v2 |
|
name: Open LLM Leaderboard |
|
- task: |
|
type: text-generation |
|
name: Text Generation |
|
dataset: |
|
name: Winogrande (5-shot) |
|
type: winogrande |
|
config: winogrande_xl |
|
split: validation |
|
args: |
|
num_few_shot: 5 |
|
metrics: |
|
- type: acc |
|
value: 51.85 |
|
name: accuracy |
|
source: |
|
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/TinyMistral-248M-v2 |
|
name: Open LLM Leaderboard |
|
- task: |
|
type: text-generation |
|
name: Text Generation |
|
dataset: |
|
name: GSM8k (5-shot) |
|
type: gsm8k |
|
config: main |
|
split: test |
|
args: |
|
num_few_shot: 5 |
|
metrics: |
|
- type: acc |
|
value: 0.0 |
|
name: accuracy |
|
source: |
|
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/TinyMistral-248M-v2 |
|
name: Open LLM Leaderboard |
|
--- |
|
# 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. 🔥 |
|
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) |
|
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Locutusque__TinyMistral-248M-v2) |
|
|
|
| Metric |Value| |
|
|---------------------------------|----:| |
|
|Avg. |28.78| |
|
|AI2 Reasoning Challenge (25-Shot)|21.25| |
|
|HellaSwag (10-Shot) |26.56| |
|
|MMLU (5-Shot) |23.39| |
|
|TruthfulQA (0-shot) |49.60| |
|
|Winogrande (5-shot) |51.85| |
|
|GSM8k (5-shot) | 0.00| |
|
|
|
|