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Open-weight model

mistral-7b-qlora-ai2_arc-full-mcqa-adapter

by Seongmin Kim mrseongminkim/mistral-7b-qlora-ai2_arc-full-mcqa-adapter

mistral-7b-qlora-ai2_arc-full-mcqa-adapter is an open-weight model from Seongmin Kim. Its published files total 87.5 MB.

This is the model card of a transformers model that has been pushed on the Hub. Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. Use the code below to get started with the model.

Parameters—
Context—
Weights83.9 MB
License—
AccessOpen weights
Monthly Downloads—

Model Card

This is the model card of a transformers model that has been pushed on the Hub. Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. Use the code below to get started with the model. Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

Excerpt from the card by Seongmin Kim.

Identity and Version

Repository
mrseongminkim/mistral-7b-qlora-ai2_arc-full-mcqa-adapter
Publisher
Seongmin Kim
Task
Not stated by the source
Modality
Other
Library
transformers
Parameters
Not stated by the source
Languages
Not stated by the source
Revision
66b4bcbc56dcf4dd8d762360339b4aae1ed11bfa
First published
2026-09-26
Last updated
2026-09-26

Files and Weights

6 files, 87.5 MB in total. The weights are 1 file totalling 83.9 MB in safetensors.

Weights1 file · 83.9 MB
Configuration1 file · 1.2 KB
Tokenizer2 files · 3.5 MB
Documentation1 file · 5.2 KB
Repository1 file · 1.5 KB
Every file
FileTypeSizeSHA-256
adapter_model.safetensorsWeights83.9 MB 2ab66abaa55c
adapter_config.jsonConfiguration1.2 KB —
README.mdDocumentation5.2 KB —
.gitattributesRepository1.5 KB —
tokenizer.jsonTokenizer3.5 MB —
tokenizer_config.jsonTokenizer493 B —

License and Download

License
Not stated by the source
Access
Open weights, no gate
Download size
83.9 MB
Download from Seongmin Kim

Released by Seongmin Kim through its official repository on Hugging Face.

Built From

Memory Requirements

PrecisionWeights in memory
As published83.9 MB

Weights only, from the published parameter count; the key-value cache and runtime add to this.