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TinyMistral 248Mx4 MoE Not Tuned Pls Help by gate369

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  Autotrain compatible Base model:jtatman/tinymistral... Base model:locutusque/tinymist... Base model:locutusque/tinymist... Base model:m4-ai/tinymistral-2... Base model:merge:jtatman/tinym... Base model:merge:locutusque/ti... Base model:merge:locutusque/ti... Base model:merge:m4-ai/tinymis...   Endpoints compatible   Frankenmoe   Instruct Jtatman/tinymistral-v2-pycoder...   Lazymergekit Locutusque/tinymistral-248m-in... Locutusque/tinymistral-248m-v2... M4-ai/tinymistral-248m-v2-clea...   Merge   Mergekit   Mixtral   Model-index   Moe   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/gate369/TinyMistral-248Mx4-MOE-not-tuned-pls-help 

TinyMistral 248Mx4 MoE Not Tuned Pls Help Benchmarks

LLME Score: 0.16937
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
TinyMistral 248Mx4 MoE Not Tuned Pls Help (gate369/TinyMistral-248Mx4-MOE-not-tuned-pls-help)

TinyMistral 248Mx4 MoE Not Tuned Pls Help Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
research, commercial applications
Applications:
chatbots, language understanding, content generation
Primary Use Cases:
assistive writing, informative responses
Additional Notes 
TinyMistral-248Mx4-MOE is an MoE model that utilizes a combination of multiple expert models to boost performance over various tasks.
Input Output 
Input Format:
JSON-like structure for chat inputs
Accepted Modalities:
text
Output Format:
textual response
Performance Tips:
For best performance, set temperature=0.7, top_k=50, top_p=0.95
LLM NameTinyMistral 248Mx4 MoE Not Tuned Pls Help
Repository 🤗https://huggingface.co/gate369/TinyMistral-248Mx4-MOE-not-tuned-pls-help 
Base Model(s)  M4-ai/TinyMistral-248M-v2-cleaner   TinyMistral 248M Instruct   jtatman/tinymistral-v2-pycoder-instuct-248m   TinyMistral 248M V2 Instruct   M4-ai/TinyMistral-248M-v2-cleaner   Locutusque/TinyMistral-248M-Instruct   jtatman/tinymistral-v2-pycoder-instuct-248m   Locutusque/TinyMistral-248M-v2-Instruct
Model Size701.1m
Required VRAM1.4 GB
Updated2024-12-21
Maintainergate369
Model Typemixtral
Instruction-BasedYes
Model Files  1.4 GB: 1-of-1
Model ArchitectureMixtralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.36.2
Tokenizer ClassLlamaTokenizer
Padding Token<|bos|>
Vocabulary Size32005
Torch Data Typefloat16

Rank the TinyMistral 248Mx4 MoE Not Tuned Pls Help Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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Release v20241217
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