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35B Beta2ep by CausalLM

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  Autotrain compatible   Cohere   Conversational   Dataset:baai/coig Dataset:causallm/refined-anime... Dataset:garage-baind/open-plat... Dataset:jondurbin/airoboros-3.... Dataset:josephuscheung/guanaco...   Dataset:ldjnr/puffin   Dataset:liwu/mnbvc Dataset:m-a-p/codefeedback-fil...   Dataset:meta-math/metamathqa Dataset:microsoft/orca-math-wo... Dataset:milashkaarshif/moegirl...   Dataset:ryokoai/fandom23k   Dataset:ryokoai/sharegpt52k   Dataset:teknium/openhermes Dataset:tigerresearch/tigerbot...   Dataset:wiki lingua   Dataset:wikipedia Dataset:wizardlm/wizardlm evol...   De   En   Endpoints compatible   Instruct   Ja   Region:us   Safetensors   Sharded   Tensorflow   Zh
Model Card on HF 🤗: https://huggingface.co/CausalLM/35b-beta2ep 

35B Beta2ep Benchmarks

ARC: 64.42 vs 96.7 (so35)-33.4%
HellaSwag: 83.74 vs 95.3 (gpt4)-12.1%
MMLU: 79.5 vs 88.3 (so35)-10%
TruthfulQA: 59.77 vs 59 (gpt4)1.3%
WinoGrande: 78.45 vs 87.5 (gpt4)-10.3%
GSM8K: 43.29 vs 96.4 (so35)-55.1%
LLME Score: 0.16213
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
35B Beta2ep (CausalLM/35b-beta2ep)
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35B Beta2ep Parameters and Internals

Additional Notes 
No loras, no quants, no tricks. Recommended for general tasks, knowledge, coding.
Supported Languages 
en (full), zh (full), ja (full), de (full)
Training Details 
Data Sources:
JosephusCheung/GuanacoDataset, meta-math/MetaMathQA, jondurbin/airoboros-3.1, WizardLM/WizardLM_evol_instruct_V2_196k, RyokoAI/ShareGPT52K, RyokoAI/Fandom23K, milashkaarshif/MoeGirlPedia_wikitext_raw_archive, wikipedia, wiki_lingua, garage-bAInd/Open-Platypus, LDJnr/Puffin, BAAI/COIG, TigerResearch/tigerbot-zhihu-zh-10k, liwu/MNBVC, teknium/openhermes, CausalLM/Refined-Anime-Text, microsoft/orca-math-word-problems-200k, m-a-p/CodeFeedback-Filtered-Instruction
Methodology:
Fully fine-tuned at 128K+ ~30M entries long, web crawl input, GPT-4-32k/3.5-16k output, synthetic dataset
Context Length:
128000
Training Time:
1 epoch
Input Output 
Input Format:
web crawl input, synthetic dataset
Output Format:
GPT-4-32k/3.5-16k output
LLM Name35B Beta2ep
Repository 🤗https://huggingface.co/CausalLM/35b-beta2ep 
Model Size35b
Required VRAM69.5 GB
Updated2025-09-23
MaintainerCausalLM
Model Typecohere
Instruction-BasedYes
Model Files  4.7 GB: 1-of-15   4.9 GB: 2-of-15   4.9 GB: 3-of-15   4.9 GB: 4-of-15   4.9 GB: 5-of-15   4.9 GB: 6-of-15   4.9 GB: 7-of-15   4.9 GB: 8-of-15   4.9 GB: 9-of-15   4.9 GB: 10-of-15   4.9 GB: 11-of-15   4.9 GB: 12-of-15   4.9 GB: 13-of-15   4.9 GB: 14-of-15   1.1 GB: 15-of-15
Supported Languagesen zh ja de
Model ArchitectureCohereForCausalLM
Licensegpl-3.0
Context Length8192
Model Max Length8192
Transformers Version4.38.2
Tokenizer ClassLlamaTokenizer
Padding Token<PAD>
Vocabulary Size256000
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than CausalLM/35b-beta2ep.

Rank the 35B Beta2ep 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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