14B by CausalLM

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  Autotrain compatible   Causallm   Dataset:baai/coig   Dataset:fnlp/moss-003-sft-data Dataset:garage-baind/open-plat... Dataset:jondurbin/airoboros-3.... Dataset:josephuscheung/guanaco...   Dataset:ldjnr/puffin Dataset:liuhaotian/llava-instr...   Dataset:liwu/mnbvc   Dataset:meta-math/metamathqa Dataset:milashkaarshif/moegirl...   Dataset:open-orca/openorca   Dataset:openbmb/llava zh   Dataset:ryokoai/fandom23k   Dataset:ryokoai/sharegpt52k   Dataset:stingning/ultrachat   Dataset:teknium/openhermes Dataset:tigerresearch/tigerbot...   Dataset:wiki lingua   Dataset:wikipedia Dataset:wizardlm/wizardlm evol...   En   Endpoints compatible   Instruct   Llama   Llama2   Pytorch   Qwen   Region:us   Sharded   Zh
Model Card on HF ๐Ÿค—: https://huggingface.co/CausalLM/14B 

14B Benchmarks

14B (CausalLM/14B)

14B Parameters and Internals

Model Type 
text-generation, causallm
Use Cases 
Areas:
Research, Commercial applications
Primary Use Cases:
Speculative sampling
Limitations:
May produce hallucinations or unreliable outputs, Contains objectionable content, pornography, violence, and offensive language
Considerations:
Conduct own safety checks, filter keywords
Additional Notes 
The model is not recommended for quantization, but rather using smaller size models like 7B.
Supported Languages 
en (English), zh (Chinese)
Training Details 
Data Sources:
JosephusCheung/GuanacoDataset, Open-Orca/OpenOrca, stingning/ultrachat, meta-math/MetaMathQA, liuhaotian/LLaVA-Instruct-150K, jondurbin/airoboros-3.1, WizardLM/WizardLM_evol_instruct_V2_196k, RyokoAI/ShareGPT52K, RyokoAI/Fandom23K, milashkaarshif/MoeGirlPedia_wikitext_raw_archive, wikipedia, wiki_lingua, fnlp/moss-003-sft-data, garage-bAInd/Open-Platypus, LDJnr/Puffin, openbmb/llava_zh, BAAI/COIG, TigerResearch/tigerbot-zhihu-zh-10k, liwu/MNBVC, teknium/openhermes
Data Volume:
1.3B tokens
Methodology:
Manual or synthetic rewrites, augmented text training, synthetic Wikipedia conversation dataset
Model Architecture:
Identical to LLaMA2, using same attention calculation method
Input Output 
Input Format:
[chatml](https://github.com/openai/openai-python/blob/main/chatml.md)
Accepted Modalities:
text
Output Format:
text
Performance Tips:
If VRAM is insufficient, use the 7B model instead of the quantized version.
Release Notes 
Version:
14B-DPO-alpha
Date:
Dec 3, 2023
Notes:
Outperforms Zephyr-ฮฒ in MT-Bench.
LLM Name14B
Repository ๐Ÿค—https://huggingface.co/CausalLM/14B 
Model Size14b
Required VRAM28.4 GB
Updated2024-12-21
MaintainerCausalLM
Model Typellama
Instruction-BasedYes
Model Files  10.0 GB: 1-of-3   10.0 GB: 2-of-3   8.4 GB: 3-of-3
Supported Languagesen zh
Model ArchitectureLlamaForCausalLM
Licensewtfpl
Context Length8192
Model Max Length8192
Transformers Version4.35.0.dev0
Tokenizer ClassGPT2Tokenizer
Vocabulary Size152064
Torch Data Typebfloat16

Quantized Models of the 14B

Model
Likes
Downloads
VRAM
CausalLM 14B GGUF161871388 GB
CausalLM 14B EXL23708 GB
CausalLM 14B GPTQ20399 GB
CausalLM 14B AWQ10459 GB

Best Alternatives to 14B

Best Alternatives
Context / RAM
Downloads
Likes
CausalLM 14B EXL28K / 8.5 GB703
CausalLM 14B GPTQ8K / 9.7 GB3920
CausalLM 14B AWQ8K / 9.7 GB4510

Rank the 14B 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241217