32bit Autotrain compatible Conversational Endpoints compatible Llama Pytorch Quantized Region:us Sharded
Model Card on HF 🤗: https://huggingface.co/MNCJihun/Mistral-7B-OpenOrca-eng-kor-combined
Mistral 7B OpenOrca Eng Kor Combined 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)
Mistral 7B OpenOrca Eng Kor Combined Parameters and Internals
| LLM Name | Mistral 7B OpenOrca Eng Kor Combined |
| Repository 🤗 | https://huggingface.co/MNCJihun/Mistral-7B-OpenOrca-eng-kor-combined |
| Model Size | 7b |
| Required VRAM | 14.4 GB |
| Updated | 2025-08-20 |
| Maintainer | MNCJihun |
| Model Type | llama |
| Model Files | |
| Quantization Type | 32bit |
| Model Architecture | LlamaForCausalLM |
| Context Length | 32768 |
| Model Max Length | 32768 |
| Transformers Version | 4.34.0 |
| Tokenizer Class | LlamaTokenizer |
| Padding Token | [PAD] |
| Vocabulary Size | 32002 |
| Torch Data Type | bfloat16 |
Best Alternatives to Mistral 7B OpenOrca Eng Kor Combined
Best Alternatives |
Context / RAM |
Downloads |
Likes |
|---|---|---|---|
| Smaugv0.1 6.0bpw H6 EXL2 | 195K / 26.4 GB | 5 | 4 |
| Smaugv0.1 5.0bpw H6 EXL2 | 195K / 22.3 GB | 5 | 3 |
| Smaugv0.1 3.0bpw H6 EXL2 | 195K / 13.9 GB | 5 | 1 |
| Smaugv0.1 4.65bpw H6 EXL2 | 195K / 20.8 GB | 5 | 1 |
| Smaugv0.1 8.0bpw H8 EXL2 | 195K / 34.9 GB | 5 | 1 |
| Smaugv0.1 4.0bpw H6 EXL2 | 195K / 18 GB | 4 | 1 |
| DeepSeek Prover V2 7B 4bit | 64K / 3.9 GB | 871 | 4 |
| Mistral 7B Openplatypus 1K | 32K / 29 GB | 1609 | 0 |
| Mistral 7B OpenOrca 1K | 32K / 29 GB | 1615 | 3 |
| ...rnlm2 20B Llama 4.0bpw H6 EXL2 | 32K / 11 GB | 5 | 1 |
Note: green Score (e.g. "73.2") means that the model is better than MNCJihun/Mistral-7B-OpenOrca-eng-kor-combined .
Rank the Mistral 7B OpenOrca Eng Kor Combined Capabilities
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124