A curated collection of datasets in French, designed to evaluate biases in LLMs
Irina Proskurina PRO
iproskurina
AI & ML interests
LLMs: quantization, pre-training
Recent Activity
updated
a model
7 days ago
iproskurina/output_llama13b_1_4_alpha_1
published
a model
7 days ago
iproskurina/output_llama13b_1_4_alpha_1
updated
a model
7 days ago
iproskurina/output_llama13b_1_4_alpha_0
Organizations
Attention graph features extracted from LMs fine-tuned on linguistic acceptability corpora
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iproskurina/tda-ruroberta-large-ru-cola
Text Classification • 0.4B • Updated • 8 -
iproskurina/tda-bert-en-cola
Text Classification • 0.1B • Updated • 100 -
iproskurina/tda-roberta-large-en-cola
Text Classification • 0.4B • Updated • 13 -
iproskurina/tda-rubert-ru-cola
Text Classification • 0.2B • Updated • 16
A collection of models submitted to the BabyLM23 competition
LLMs quantized with GPTQ
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iproskurina/Mistral-7B-v0.3-GPTQ-4bit-g128
Text Generation • 7B • Updated • 43 -
iproskurina/bloom-7b1-GPTQ-4bit-g128
Text Generation • 3B • Updated • 23 • 2 -
iproskurina/bloom-1b7-GPTQ-4bit-g128
Text Generation • 1B • Updated • 29 -
iproskurina/bloom-3b-GPTQ-4bit-g128
Text Generation • 2B • Updated • 28
A curated collection of datasets in French, designed to evaluate biases in LLMs
LLMs quantized with GPTQ
-
iproskurina/Mistral-7B-v0.3-GPTQ-4bit-g128
Text Generation • 7B • Updated • 43 -
iproskurina/bloom-7b1-GPTQ-4bit-g128
Text Generation • 3B • Updated • 23 • 2 -
iproskurina/bloom-1b7-GPTQ-4bit-g128
Text Generation • 1B • Updated • 29 -
iproskurina/bloom-3b-GPTQ-4bit-g128
Text Generation • 2B • Updated • 28
Attention graph features extracted from LMs fine-tuned on linguistic acceptability corpora
-
iproskurina/tda-ruroberta-large-ru-cola
Text Classification • 0.4B • Updated • 8 -
iproskurina/tda-bert-en-cola
Text Classification • 0.1B • Updated • 100 -
iproskurina/tda-roberta-large-en-cola
Text Classification • 0.4B • Updated • 13 -
iproskurina/tda-rubert-ru-cola
Text Classification • 0.2B • Updated • 16
A collection of models submitted to the BabyLM23 competition