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Panther V1 by Rardilit

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  Autotrain compatible Dataset:rardilit/panther-datas...   En   Endpoints compatible   Llama   Panther   Pytorch   Region:us   Tensorboard
Model Card on HF 🤗: https://huggingface.co/Rardilit/Panther_v1 

Panther V1 Benchmarks

LLME Score: 0.09596
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Panther V1 (Rardilit/Panther_v1)
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Panther V1 Parameters and Internals

Model Type 
Transformer-based Language Model
Use Cases 
Primary Use Cases:
Text generation, Exploring characteristics of language generated by a language model
Limitations:
Usage in biomedical, political, legal, or financial domains
Supported Languages 
en (fluent)
Training Details 
Data Sources:
Rardilit/Panther-dataset_v1
Data Volume:
20k prompts and responses
Methodology:
Low-rank adapter for LLaMA-7b
Training Time:
approx. 45 min on 1 x T4 16gb vRAM
Hardware Used:
1 x T4 16gb vRAM
Model Architecture:
LORA adapter with parameters: LORA_R = 8, LORA_ALPHA = 16, LORA_DROPOUT= 0.05
LLM NamePanther V1
Repository 🤗https://huggingface.co/Rardilit/Panther_v1 
Required VRAM0 GB
Updated2025-09-23
MaintainerRardilit
Model Typellama
Model Files  0.0 GB   0.0 GB   0.0 GB   0.0 GB   0.0 GB
Supported Languagesen
Model ArchitectureLLaMAForCausalLM
Licenseother
Context Length2048
Model Max Length2048
Transformers Version4.30.0.dev0
Tokenizer ClassLlamaTokenizer
Beginning of Sentence Token<s>
End of Sentence Token</s>
Unk Token<unk>
Vocabulary Size32000
Torch Data Typefloat16

Best Alternatives to Panther V1

Best Alternatives
Context / RAM
Downloads
Likes
BigTranslate0K / 26.5 GB86550
Toolpaca0K / 52.1 GB737
Gpt4 X Alpaca0K / 52.1 GB61
Guanaco Dumbdumb0K / 0 GB61
Llama13b 4bit V20K / 7 GB175
Note: green Score (e.g. "73.2") means that the model is better than Rardilit/Panther_v1.

Rank the Panther V1 Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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 v20241124
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