Add SetFit model
Browse files- README.md +58 -57
- model_head.pkl +1 -1
- pytorch_model.bin +1 -1
README.md
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@@ -15,35 +15,36 @@ metrics:
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- F1-Score
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- accuracy
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widget:
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pipeline_tag: text-classification
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inference: false
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base_model: sentence-transformers/all-mpnet-base-v2
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split: test
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metrics:
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- type: Precision_micro
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value: 0.
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name: Precision_Micro
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- type: Precision_weighted
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value: 0.
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name: Precision_Weighted
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- type: Precision_samples
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value: 0.
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name: Precision_Samples
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- type: Recall_micro
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value: 0.
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name: Recall_Micro
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- type: Recall_weighted
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value: 0.
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name: Recall_Weighted
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- type: Recall_samples
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value: 0.
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name: Recall_Samples
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- type: F1-Score
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value: 0.
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name: F1-Score
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- type: accuracy
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value: 0.
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name: Accuracy
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---
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@@ -116,7 +117,7 @@ The model has been trained using an efficient few-shot learning technique that i
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### Metrics
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| Label | Precision_Micro | Precision_Weighted | Precision_Samples | Recall_Micro | Recall_Weighted | Recall_Samples | F1-Score | Accuracy |
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|:--------|:----------------|:-------------------|:------------------|:-------------|:----------------|:---------------|:---------|:---------|
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| **all** | 0.
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## Uses
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@@ -136,7 +137,7 @@ from setfit import SetFitModel
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# Download from the 🤗 Hub
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model = SetFitModel.from_pretrained("leavoigt/vulnerability_target")
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# Run inference
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preds = model("
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```
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<!--
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### Training Set Metrics
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| Training set | Min | Median | Max |
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|:-------------|:----|:--------|:----|
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| Word count | 15 |
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### Training Hyperparameters
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- batch_size: (16, 16)
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### Training Results
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| Epoch | Step | Training Loss | Validation Loss |
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|:------:|:----:|:-------------:|:---------------:|
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| 0.0012 | 1 | 0.
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| 0.0602 | 50 | 0.
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| 0.1205 | 100 | 0.
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| 0.1807 | 150 | 0.
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| 0.2410 | 200 | 0.
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| 0.3012 | 250 | 0.
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| 0.3614 | 300 | 0.
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| 0.4217 | 350 | 0.
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| 0.4819 | 400 | 0.
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| 0.5422 | 450 | 0.
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| 0.6024 | 500 | 0.
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| 0.6627 | 550 | 0.
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| 0.7229 | 600 | 0.
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| 0.7831 | 650 | 0.
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| 0.8434 | 700 | 0.
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| 0.9036 | 750 | 0.
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| 0.9639 | 800 | 0.
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### Framework Versions
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- Python: 3.10.12
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- F1-Score
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- accuracy
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widget:
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- text: To support the traditional knowledge and adaptive capacity of indigenous peoples
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in the face of climate change, we aim to establish 50 community-based adaptation
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projects led by indigenous peoples by 2030, focusing on the sustainable management
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of natural resources and the preservation of cultural practices.
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- text: Measures related to climate change are incorporated into national policies,
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strategies and plans. In this regard, mechanisms are also promoted to increase
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capacity for effective planning and management in relation to climate change.
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SDG No. 14 (Marine life). Adaptation. There is a link between the Coastal Marine
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Resources sector in the measures proposed in this document and the indicators
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of this SDG regarding the sustainable management and conservation of marine and
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coastal ecosystems to achieve an increase in their climate resilience. SDG No.
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- text: ' Pathways with higher demand for food, feed, and water, more resource-intensive
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consumption and production, and more limited technological improvements in agriculture
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yields result in higher risks from water scarcity in drylands, land degradation,
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and food insecurity 1. This means that communities that rely on agriculture for
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their livelihoods are at risk of losing their crops and experiencing food shortages
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due to climate change.'
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- text: The population aged 60 years and above is projected to increase from almost
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one million (988,000) in 2000 to over six million (6,319,000) by 2050. The female
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aged population will continue to grow faster and will increasingly be far higher
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than the male population for the advanced ages. Policies addressing the needs
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of the elderly will have to take the sex structure of the aged population into
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consideration.
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- text: Indigenous peoples who choose or are forced to migrate away from their traditional
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lands often face double discrimination as both migrants and as indigenous peoples.
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Indigenous peoples may be more vulnerable to irregular migration such as trafficking
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and smuggling, owing to sudden displacement by a climactic event, limited legal
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migration options and limited opportunities to make informed choices. Deforestation,
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particularly in developing countries, is pushing indigenous families to migrate
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to cities for economic reasons, often ending up in urban slums.
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pipeline_tag: text-classification
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inference: false
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base_model: sentence-transformers/all-mpnet-base-v2
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split: test
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metrics:
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- type: Precision_micro
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value: 0.7762237762237763
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name: Precision_Micro
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- type: Precision_weighted
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value: 0.7968800430338892
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name: Precision_Weighted
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- type: Precision_samples
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value: 0.7762237762237763
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name: Precision_Samples
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- type: Recall_micro
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value: 0.7762237762237763
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name: Recall_Micro
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- type: Recall_weighted
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value: 0.7762237762237763
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name: Recall_Weighted
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- type: Recall_samples
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value: 0.7762237762237763
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name: Recall_Samples
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- type: F1-Score
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value: 0.7762237762237763
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name: F1-Score
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- type: accuracy
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value: 0.7762237762237763
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name: Accuracy
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---
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### Metrics
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| Label | Precision_Micro | Precision_Weighted | Precision_Samples | Recall_Micro | Recall_Weighted | Recall_Samples | F1-Score | Accuracy |
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|:--------|:----------------|:-------------------|:------------------|:-------------|:----------------|:---------------|:---------|:---------|
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| **all** | 0.7762 | 0.7969 | 0.7762 | 0.7762 | 0.7762 | 0.7762 | 0.7762 | 0.7762 |
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## Uses
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# Download from the 🤗 Hub
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model = SetFitModel.from_pretrained("leavoigt/vulnerability_target")
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# Run inference
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preds = model("To support the traditional knowledge and adaptive capacity of indigenous peoples in the face of climate change, we aim to establish 50 community-based adaptation projects led by indigenous peoples by 2030, focusing on the sustainable management of natural resources and the preservation of cultural practices.")
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```
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<!--
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### Training Set Metrics
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| Training set | Min | Median | Max |
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|:-------------|:----|:--------|:----|
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+
| Word count | 15 | 70.8675 | 238 |
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### Training Hyperparameters
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- batch_size: (16, 16)
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### Training Results
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| Epoch | Step | Training Loss | Validation Loss |
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|:------:|:----:|:-------------:|:---------------:|
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| 0.0012 | 1 | 0.3493 | - |
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| 0.0602 | 50 | 0.2285 | - |
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| 0.1205 | 100 | 0.1092 | - |
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| 0.1807 | 150 | 0.1348 | - |
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| 0.2410 | 200 | 0.0365 | - |
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| 0.3012 | 250 | 0.0052 | - |
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| 0.3614 | 300 | 0.0012 | - |
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| 0.4217 | 350 | 0.0031 | - |
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| 0.4819 | 400 | 0.0001 | - |
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| 0.5422 | 450 | 0.0011 | - |
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| 0.6024 | 500 | 0.0001 | - |
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| 0.6627 | 550 | 0.0001 | - |
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| 0.7229 | 600 | 0.0001 | - |
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| 0.7831 | 650 | 0.0002 | - |
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| 0.8434 | 700 | 0.0001 | - |
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| 0.9036 | 750 | 0.0001 | - |
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| 0.9639 | 800 | 0.0001 | - |
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### Framework Versions
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- Python: 3.10.12
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model_head.pkl
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version https://git-lfs.github.com/spec/v1
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size 13956
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version https://git-lfs.github.com/spec/v1
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size 13956
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pytorch_model.bin
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