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Finance Chat by AdaptLLM

 »  All LLMs  »  AdaptLLM  »  Finance Chat   URL Share it on

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  Arxiv:2309.09530   Autotrain compatible   Dataset:gair/lima   Dataset:open-orca/openorca Dataset:wizardlm/wizardlm evol...   En   Endpoints compatible   Finance   Instruct   Llama   Model-index   Pytorch   Region:us   Safetensors   Sharded   Tensorflow

Finance Chat Benchmarks

ARC: 53.75-44.2%
HellaSwag: 76.6-19.6%
MMLU: 50.16-42%
TruthfulQA: 44.54-24.5%
WinoGrande: 75.69-13.5%
GSM8K: 18.8-79.6%
nn.n% — How the model compares to the GPT-4.

Finance Chat Parameters and Internals

LLM NameFinance Chat
RepositoryOpen on 🤗 
Model Size6.7b
Required VRAM27 GB
Updated2024-07-27
MaintainerAdaptLLM
Model Typellama
Instruction-BasedYes
Model Files  9.9 GB: 1-of-3   9.9 GB: 2-of-3   7.2 GB: 3-of-3   9.9 GB: 1-of-3   9.9 GB: 2-of-3   7.2 GB: 3-of-3
Supported Languagesen
Model ArchitectureLlamaForCausalLM
Licensellama2
Context Length4096
Model Max Length4096
Transformers Version4.31.0.dev0
Tokenizer ClassLlamaTokenizer
Beginning of Sentence Token<s>
End of Sentence Token</s>
Padding Token<pad>
Unk Token<unk>
Vocabulary Size32001
Torch Data Typefloat16
Finance Chat (AdaptLLM/finance-chat)

Quantized Models of the Finance Chat

Model
Likes
Downloads
VRAM
Finance Chat GGUF102152 GB
Finance Chat AWQ3123 GB
Finance Chat GPTQ3103 GB

Best Alternatives to Finance Chat

Best Alternatives
HF Rank
Context/RAM
Downloads
Likes
Magicoder S DS 6.7B0.316K / 27.1 GB3285200
Code 290K 6.7B Instruct0.316K / 13.5 GB2996
Speechless Coder Ds 6.7B0.316K / 13.5 GB9355
Datascience Coder 6.7B0.216K / 13.5 GB9303
Merge Code Gen0.216K / 13.6 GB140
... 6.7B Instruct Trt Int4 G64 Hf0.216K / 4.2 GB70
...d Llama 6.7B RAG Code Instruct0.216K / 13.5 GB71
...6.7B Instruct Trt Int8 G128 Hf0.216K / 7.2 GB70
AIGCodeGeek DS 6.7B0.216K / 13.5 GB93
Magicoder S DS 6.7B MLX0.216K / 13.4 GB111
Note: green Score (e.g. "73.2") means that the model is better than AdaptLLM/finance-chat.

Rank the Finance Chat 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 v2024072501
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