Binary Clumsy Bear Benchmarks
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)
Binary Clumsy Bear Parameters and Internals
| LLM Name | Binary Clumsy Bear |
| Repository 🤗 | https://huggingface.co/samvelkoch/binary-clumsy-bear |
| Model Size | 1.8b |
| Required VRAM | 7.3 GB |
| Updated | 2024-10-18 |
| Maintainer | samvelkoch |
| Model Type | mistral |
| Model Files | |
| Supported Languages | en |
| Model Architecture | MistralForCausalLM |
| Context Length | 8192 |
| Model Max Length | 8192 |
| Transformers Version | 4.40.2 |
| Tokenizer Class | LlamaTokenizer |
| Padding Token | <unk> |
| Vocabulary Size | 32000 |
| Torch Data Type | float32 |
Best Alternatives to Binary Clumsy Bear
Best Alternatives |
Context / RAM |
Downloads |
Likes |
|---|---|---|---|
| H2o Danube 1.8B Base | 16K / 3.7 GB | 1004 | 43 |
| H2o Danube 1.8B Chat | 16K / 3.7 GB | 651 | 55 |
| H2o Danube 1.8B Sft | 16K / 3.7 GB | 501 | 11 |
| Cypher Mini 1.8B | 16K / 3.7 GB | 70 | 2 |
| PixieZehirNano | 16K / 3.7 GB | 10 | 0 |
| Cypher CoT 1.8B | 16K / 3.7 GB | 9 | 1 |
| ...1.8B Chat Sft Merge Fourier V1 | 16K / 7.3 GB | 5 | 1 |
| H2o Danube2 1.8B Chat | 8K / 3.7 GB | 5217 | 58 |
| H2o Danube2 1.8B Base | 8K / 3.7 GB | 1767 | 46 |
| H2o Danube2 1.8B Sft | 8K / 3.7 GB | 553 | 6 |
Note: green Score (e.g. "73.2") means that the model is better than samvelkoch/binary-clumsy-bear .
Rank the Binary Clumsy Bear Capabilities
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v2024072803