
# bertweet-base-multi-mami
This is a Bertweet model: It maps sentences & paragraphs to a 768 dimensional dense vector space and classifies them into 5 multi labels.

# Multilabels
    label2id={
        "misogynous": 0,
        "shaming": 1,
        "stereotype": 2,
        "objectification": 3,
        "violence": 4,
    },

{"language": "en", "license": "apache-2.0", "tags": ["text-classification", "misogyny"], "pipeline_tag": "text-classification", "widget": [{"text": "Women wear yoga pants because men don't stare at their personality", "example_title": "Misogyny detection"}]}
transformers pytorch safetensors roberta text-classification misogyny en license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #safetensors #roberta #text-classification #misogyny #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 


# bertweet-base-multi-mami
This is a Bertweet model: It maps sentences & paragraphs to a 768 dimensional dense vector space and classifies them into 5 multi labels.

# Multilabels
    label2id={
        "misogynous": 0,
        "shaming": 1,
        "stereotype": 2,
        "objectification": 3,
        "violence": 4,
    },

# bertweet-base-multi-mami
This is a Bertweet model: It maps sentences & paragraphs to a 768 dimensional dense vector space and classifies them into 5 multi labels. # Multilabels
    label2id={
        "misogynous": 0,
        "shaming": 1,
        "stereotype": 2,
        "objectification": 3,
        "violence": 4,
    },
TAGS
#transformers #pytorch #safetensors #roberta #text-classification #misogyny #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 # bertweet-base-multi-mami
This is a Bertweet model: It maps sentences & paragraphs to a 768 dimensional dense vector space and classifies them into 5 multi labels. # Multilabels
    label2id={
        "misogynous": 0,
        "shaming": 1,
        "stereotype": 2,
        "objectification": 3,
        "violence": 4,
    },
passage: TAGS
#transformers #pytorch #safetensors #roberta #text-classification #misogyny #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
# bertweet-base-multi-mami
This is a Bertweet model: It maps sentences & paragraphs to a 768 dimensional dense vector space and classifies them into 5 multi labels.# Multilabels
    label2id={
        "misogynous": 0,
        "shaming": 1,
        "stereotype": 2,
        "objectification": 3,
        "violence": 4,
    },