What are the hardware requirements for Finance Qa Model?

Finance Qa Model requires approximately 4.7 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Finance Qa Model and how large is it?

Finance Qa Model is developed by jiweiwuita, a model with 7b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Finance Qa Model?

Finance Qa Model is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Finance Qa Model by jiweiwuita — VRAM 4.7GB

Name: Finance Qa Model
Author: jiweiwuita

Finance Qa Model is an open-source language model by jiweiwuita. Features: 7b LLM, VRAM: 4.7GB, License: apache-2.0, Quantized, LLM Explorer Score: 0.13.

4bit Base model:quantized:unsloth/q... Base model:unsloth/qwen2-7b-bn... En Endpoints compatible Gguf Quantized Qwen2 Region:us Unsloth

Model Card on HF 🤗: https://huggingface.co/jiweiwuita/finance-qa-model

Finance Qa Model Parameters and Internals

LLM Name	Finance Qa Model
Repository 🤗	https://huggingface.co/jiweiwuita/finance-qa-model
Base Model(s)	Qwen2 7B Bnb 4bit unsloth/Qwen2-7B-bnb-4bit
Model Size	7b
Required VRAM	4.7 GB
Updated	2024-07-30
Maintainer	jiweiwuita
Model Type	qwen2
Model Files	4.7 GB
Supported Languages	en
GGUF Quantization	Yes
Quantization Type	gguf\|4bit
Model Architecture	AutoModel
License	apache-2.0

Rank the Finance Qa Model capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

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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Note: green Score (e.g. "73.2") means that the model is better than jiweiwuita/finance-qa-model.