Selfbot 256 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)
Selfbot 256 Mistral Parameters and Internals
| LLM Name | Selfbot 256 Mistral |
| Repository 🤗 | https://huggingface.co/jeiku/selfbot_256_mistral |
| Base Model(s) | |
| Model Size | 7b |
| Required VRAM | 0.4 GB |
| Updated | 2024-09-13 |
| Maintainer | jeiku |
| Instruction-Based | Yes |
| Model Files | |
| GPTQ Quantization | Yes |
| Quantization Type | gptq |
| Model Architecture | Adapter |
| Is Biased | none |
| PEFT Type | LORA |
| LoRA Model | Yes |
| PEFT Target Modules | v_proj|q_proj |
| LoRA Alpha | 256 |
| LoRA Dropout | 0.05 |
| R Param | 256 |
Best Alternatives to Selfbot 256 Mistral
Best Alternatives |
Context / RAM |
Downloads |
Likes |
|---|---|---|---|
| Term Qwen2 7 Json Lora | 0K / 0.1 GB | 13 | 0 |
| Futadom Mistral | 0K / 0.2 GB | 3 | 1 |
| Humiliation Mistral | 0K / 0.2 GB | 2 | 1 |
| Mistral Finetuned DialogSumm | 0K / 0 GB | 16 | 1 |
| ...ralic 7B 1 GPTQ LORA CAUSAL LM | 0K / 0.3 GB | 2 | 1 |
| Mistral Numericnlg FV | 0K / 0.3 GB | 5 | 0 |
| Mistral Wikitable FV | 0K / 0.3 GB | 5 | 0 |
| Mistral Charttotext FV | 0K / 0.3 GB | 5 | 0 |
| Zephyr 7B Beta Agent Instruct | 0K / 0.3 GB | 3 | 1 |
| Falcon 7B Instruct 4bit Lora | 0K / 0 GB | 0 | 1 |
Note: green Score (e.g. "73.2") means that the model is better than jeiku/selfbot_256_mistral .
Rank the Selfbot 256 Mistral Capabilities
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241110