4-bit 4bit Autotrain compatible Base model:quantized:unsloth/m... Base model:unsloth/mistral-nem... Bitsandbytes En Endpoints compatible Lora Mistral Pytorch Quantized Region:us Safetensors Unsloth
Model Card on HF 🤗: https://huggingface.co/Zeinab321/Mistral
Mistral 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 Parameters and Internals
| LLM Name | Mistral |
| Repository 🤗 | https://huggingface.co/Zeinab321/Mistral |
| Base Model(s) | |
| Required VRAM | 0.2 GB |
| Updated | 2025-09-08 |
| Maintainer | Zeinab321 |
| Model Files | |
| Supported Languages | en |
| Quantization Type | 4bit |
| Model Architecture | AutoModelForCausalLM |
| License | apache-2.0 |
| Model Max Length | 32768 |
| Is Biased | none |
| Tokenizer Class | LlamaTokenizer |
| Padding Token | <unk> |
| PEFT Type | LORA |
| LoRA Model | Yes |
| PEFT Target Modules | gate_proj|down_proj|o_proj|up_proj|k_proj|v_proj|q_proj |
| LoRA Alpha | 16 |
| LoRA Dropout | 0 |
| R Param | 16 |
Best Alternatives to Mistral
Best Alternatives |
Context / RAM |
Downloads |
Likes |
|---|---|---|---|
| ...emo Instruct 2407 EXL2 8bpw H8 | 0K / 12.6 GB | 4 | 7 |
| Dre Phi | 0K / 7.6 GB | 5 | 0 |
| Phi 3 Mini 4K CodeInstruct | 0K / 7.6 GB | 5 | 0 |
| ...3 Mini 4K Instruct Text To Sql | 0K / 7.6 GB | 14 | 0 |
| ...ral 8x7B ZLoss 3.75bpw H6 EXL2 | 0K / 22.2 GB | 4 | 1 |
| Asdf | 0K / 0.2 GB | 72 | 0 |
| MS32 3 | 0K / 1.5 GB | 30 | 0 |
| MS32 2 | 0K / 0.7 GB | 26 | 0 |
| Phi 3 Mini 4K Python | 0K / 7.6 GB | 77 | 1 |
| Tinyllama Cpt | 0K / 0.5 GB | 8 | 0 |
Note: green Score (e.g. "73.2") means that the model is better than Zeinab321/Mistral .
Rank the Mistral Capabilities
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124