Saiga2 70B Lora By IlyaGusev: Benchmarks, Features and Detailed Analysis. Insights on Saiga2 70B Lora.

Adapter Conversational Dataset:ilyagusev/gpt roleplay... Dataset:ilyagusev/oasst1 ru ma... Dataset:ilyagusev/ru sharegpt ... Dataset:ilyagusev/ru turbo alp... Dataset:lksy/ru instruct gpt4 Finetuned Instruct Lora Region:us Ru

Saiga2 70b Lora Benchmarks

LLME Score: 0.14126

^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)

Saiga2 70B Lora Parameters and Internals

Model Type

conversational

Use Cases

Areas:

conversational AI

Primary Use Cases:

chatbot interaction

Supported Languages

ru (high)

Training Details

Data Sources:

IlyaGusev/ru_turbo_alpaca, IlyaGusev/ru_sharegpt_cleaned, IlyaGusev/oasst1_ru_main_branch, lksy/ru_instruct_gpt4, IlyaGusev/gpt_roleplay_realm

Methodology:

self_instruct

Model Architecture:

adapter-only version

Input Output

Input Format:

~~{role} {content}~~

Accepted Modalities:

text

LLM Name	Saiga2 70b Lora
Repository 🤗	https://huggingface.co/IlyaGusev/saiga2_70b_lora
Model Size	70b
Required VRAM	0.3 GB
Updated	2024-11-12
Maintainer	IlyaGusev
Instruction-Based	Yes
Model Files	0.3 GB
Supported Languages	ru
Model Architecture	Adapter
License	cc-by-4.0
Model Max Length	4096
Is Biased	none
Tokenizer Class	LlamaTokenizer
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	q_proj\|v_proj\|k_proj\|o_proj
LoRA Alpha	16
LoRA Dropout	0.05
R Param	16

Saiga2 70B Lora (IlyaGusev/saiga2_70b_lora)

Quantized Models of the Saiga2 70B Lora

Model	Likes	Downloads	VRAM
Saiga2 70b Lora GPTQ	2	28	36 GB

Best Alternatives to Saiga2 70B Lora

Best Alternatives	Context / RAM	Downloads	Likes
Llama 3 70B Instruct Spider	0K / 141.9 GB	6	0
Llama3v1	0K / 0.1 GB	10	0
LLaMA 2 Wizard 70B QLoRA	0K / 1.7 GB	0	4
Llama 2 70B Instruct V0.1	0K / 1.1 GB	104	14

Note: green Score (e.g. "73.2") means that the model is better than IlyaGusev/saiga2_70b_lora.

Rank the Saiga2 70B Lora 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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Original data from HuggingFace, OpenCompass and various public git repos.

Release v20241110

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