Model Card on HF 🤗: https://huggingface.co/jerryjalapeno/nart-7b
Nart 7B 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)
Nart 7B Parameters and Internals
| LLM Name | Nart 7B |
| Repository 🤗 | https://huggingface.co/jerryjalapeno/nart-7b |
| Model Size | 7b |
| Required VRAM | 27 GB |
| Updated | 2025-06-01 |
| Maintainer | jerryjalapeno |
| Model Type | llama |
| Model Files | |
| Model Architecture | LlamaForCausalLM |
| License | cc-by-nc-nd-4.0 |
| Context Length | 2048 |
| Model Max Length | 2048 |
| Transformers Version | 4.28.1 |
| Tokenizer Class | LlamaTokenizer |
| Beginning of Sentence Token | <s> |
| End of Sentence Token | </s> |
| Unk Token | <unk> |
| Vocabulary Size | 32000 |
| Torch Data Type | float32 |
Best Alternatives to Nart 7B
Best Alternatives |
Context / RAM |
Downloads |
Likes |
|---|---|---|---|
| A6 L | 1024K / 16.1 GB | 201 | 0 |
| M | 1024K / 16.1 GB | 127 | 0 |
| 157 | 1024K / 16.1 GB | 101 | 0 |
| 124 | 1024K / 16.1 GB | 93 | 0 |
| A3.4 | 1024K / 16.1 GB | 13 | 0 |
| A5.4 | 1024K / 16.1 GB | 12 | 0 |
| A2.4 | 1024K / 16.1 GB | 12 | 0 |
| 2 Very Sci Fi | 1024K / 16.1 GB | 317 | 0 |
| 162 | 1024K / 16.1 GB | 60 | 0 |
| 118 | 1024K / 16.1 GB | 15 | 0 |
Note: green Score (e.g. "73.2") means that the model is better than jerryjalapeno/nart-7b .
Rank the Nart 7B Capabilities
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227