Autotrain compatible Conversational Endpoints compatible Lazymergekit Merge Mergekit Mixtral Mlabonne/neuralbeagle14-7b Mlabonne/neuraldaredevil-7b Model-index Moe Region:us Safetensors Sharded Tensorflow
DareBeagel 2x7B Benchmarks
ARC: 72.01 vs 96.7 (so35)-25.5%
HellaSwag: 88.12 vs 95.3 (gpt4)-7.5%
MMLU: 64.51 vs 88.3 (so35)-26.9%
TruthfulQA: 69.09 vs 59 (gpt4)17.1%
WinoGrande: 82.72 vs 87.5 (gpt4)-5.5%
GSM8K: 70.51 vs 96.4 (so35)-26.9%
LLME Score: 0.19905
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
What is the LLM Explorer Rank (Score)
DareBeagel 2x7B Parameters and Internals
| LLM Name | DareBeagel 2x7B |
| Repository 🤗 | https://huggingface.co/shadowml/DareBeagel-2x7B |
| Model Size | 12.9b |
| Required VRAM | 25.8 GB |
| Updated | 2024-10-18 |
| Maintainer | shadowml |
| Model Type | mixtral |
| Model Files | |
| Model Architecture | MixtralForCausalLM |
| License | apache-2.0 |
| Context Length | 32768 |
| Model Max Length | 32768 |
| Transformers Version | 4.36.2 |
| Tokenizer Class | LlamaTokenizer |
| Padding Token | <s> |
| Vocabulary Size | 32000 |
| Torch Data Type | float16 |
Best Alternatives to DareBeagel 2x7B
Best Alternatives |
Context / RAM |
Downloads |
Likes |
|---|---|---|---|
| MixTAO 7Bx2 MoE V8.1 | 32K / 25.8 GB | 7695 | 53 |
| MixTAO 7Bx2 MoE V8.1 | 32K / 25.8 GB | 8760 | 52 |
| LogoS 7Bx2 MoE 13B V0.2 | 32K / 25.9 GB | 4091 | 10 |
| MultiMash8 13B Slerp | 32K / 25.7 GB | 7 | 0 |
| MultiMash11 13B Slerp | 32K / 25.7 GB | 10 | 0 |
| MultiMash9 13B Slerp | 32K / 25.7 GB | 10 | 0 |
| MultiMash10 13B Slerp | 32K / 25.7 GB | 10 | 0 |
| MixTaoTruthful 13B Slerp | 32K / 25.7 GB | 7 | 0 |
| MultiMash6 12B Slerp | 32K / 25.7 GB | 15 | 0 |
| Multimash3 12B Slerp | 32K / 25.7 GB | 5 | 0 |
Note: green Score (e.g. "73.2") means that the model is better than shadowml/DareBeagel-2x7B .
Rank the DareBeagel 2x7B Capabilities
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v2024072803