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AdaptLLM Finance Chat AWQ by msamon

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AdaptLLM Finance Chat AWQ is an open-source language model by msamon. Features: 6.7b LLM, VRAM: 3.9GB, Context: 4K, License: llama2, Quantized, Instruction-Based, LLM Explorer Score: 0.11.

  Arxiv:2309.09530   4-bit   Awq   Dataset:gair/lima   Dataset:open-orca/openorca Dataset:wizardlm/wizardlm evol...   En   Endpoints compatible   Finance   Instruct   Llama   Quantized   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/msamon/AdaptLLM-finance-chat-AWQ 

AdaptLLM Finance Chat AWQ Benchmarks

LLME Score: 0.11106
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
AdaptLLM Finance Chat AWQ (msamon/AdaptLLM-finance-chat-AWQ)
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AdaptLLM Finance Chat AWQ Parameters and Internals

Model Type 
text-generation, domain-specific
Use Cases 
Areas:
finance
Additional Notes 
Our method adapts LLaMA models to different domains such as biomedicine, finance, and law by transforming domain-specific corpora into reading comprehension tasks.
Training Details 
Data Sources:
Open-Orca/OpenOrca, GAIR/lima, WizardLM/WizardLM_evol_instruct_V2_196k
Methodology:
Continued pre-training on domain-specific corpora and adaptation via reading comprehension transformation.
Release Notes 
Version:
LLaMA-2-Chat-7B
Notes:
Released chat models developed from LLaMA-2-Chat-7B.
Version:
LLaMA-1-13B
Date:
12/19
Notes:
Released 13B base models developed from LLaMA-1-13B.
Version:
LLaMA-1-7B
Date:
9/18
Notes:
Released paper, code, data, and base models developed from LLaMA-1-7B.
LLM NameAdaptLLM Finance Chat AWQ
Repository 🤗https://huggingface.co/msamon/AdaptLLM-finance-chat-AWQ 
Model Size6.7b
Required VRAM3.9 GB
Updated2026-03-29
Maintainermsamon
Model Typellama
Instruction-BasedYes
Model Files  3.9 GB
Supported Languagesen
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureLlamaForCausalLM
Licensellama2
Context Length4096
Model Max Length4096
Transformers Version4.36.2
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size32001
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than msamon/AdaptLLM-finance-chat-AWQ.

Rank the AdaptLLM Finance Chat AWQ 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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