Arxiv:2309.12284 Autotrain compatible Dataset:meta-math/metamathqa Endpoints compatible Llama Pytorch Region:us Sharded
MetaMath Llemma 7B Benchmarks
ARC: 46.5-51.7%
HellaSwag: 61.69-35.3%
MMLU: 47.66-44.9%
TruthfulQA: 39.61-32.9%
WinoGrande: 62.75-28.3%
GSM8K: 60.96-33.7%
nn.n% — How the model compares to the GPT-4.
MetaMath Llemma 7B Parameters and Internals
| LLM Name | MetaMath Llemma 7B |
| Repository | Open on 🤗 |
| Model Size | 7b |
| Required VRAM | 27 GB |
| Updated | 2024-07-27 |
| Maintainer | meta-math |
| Model Type | llama |
| Model Files | |
| Model Architecture | LlamaForCausalLM |
| License | apache-2.0 |
| Context Length | 4096 |
| Model Max Length | 4096 |
| Transformers Version | 4.35.0.dev0 |
| Tokenizer Class | LlamaTokenizer |
| Padding Token | [PAD] |
| Vocabulary Size | 32001 |
| Torch Data Type | float32 |
Best Alternatives to MetaMath Llemma 7B
Best Alternatives |
HF Rank |
Context/RAM |
Downloads |
Likes |
|---|---|---|---|---|
| ...1M 1000000ctx AEZAKMI 3 1 1702 | 0.2 | 1024K / 13.5 GB | 296 | 1 |
| Yarn Llama 2 7B 128K | 0.2 | 128K / 13.5 GB | 12746 | 38 |
| LLaMA 7B PoSE YaRN 128K | 0.2 | 128K / 13.5 GB | 28 | 2 |
| LLaMA 7B PoSE YaRN 96K | 0.2 | 96K / 13.5 GB | 11 | 1 |
| LLaMA 7B PoSE Linear 96K | 0.2 | 96K / 27 GB | 7 | 1 |
| Chat Llama2 7B 80K | 0.2 | 80K / 13.8 GB | 11 | 0 |
| Llama2 7B 80K | 0.2 | 80K / 13.8 GB | 7 | 0 |
| Lloma Step400 | 0.3 | 64K / 13.5 GB | 306 | 0 |
| Lloma Step200 | 0.3 | 64K / 13.5 GB | 298 | 0 |
| Lloma Step50 | 0.2 | 64K / 13.5 GB | 297 | 0 |
Note: green Score (e.g. "73.2") means that the model is better than meta-math/MetaMath-Llemma-7B .
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v2024072501