Alphabet’s Google said on Tuesday it will restrict the types of election-related queries its chatbot Bard and search generative experience can return responses for, in the run up to 2024 U.S. Presidential election.
The restrictions are set to be enforced by early 2024, the company said.
Aside from the U.S., a slew of groundbreaking elections are expected…
FinBERT is a pre-trained NLP model to analyze sentiment of financial text. It is built by further training the BERT language model in the finance domain, using a large financial corpus and thereby fine-tuning it for financial sentiment classification. Financial PhraseBank by Malo et al. (2014) is used for fine-tuning. For more details, please see…
layoutlmv2-large-uncased-finetuned-vi-infovqa
This model is a fine-tuned version of microsoft/layoutlmv2-large-uncased on an unknown dataset.
It achieves the following results on the evaluation set:
Loss: 8.5806
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training…
Model
llava-internlm2-7b is a LLaVA model fine-tuned from InternLM2-Chat-7B and CLIP-ViT-Large-patch14-336 with LLaVA-Pretrain and LLaVA-Instruct by XTuner.
Results
Model
MMBench Test (EN)
MMBench Dev (EN)
MMBench Test (CN)
MMBench Dev (CN)
CCBench Dev
MME
SEEDBench_IMG
MMVet
MMMU Dev
MathVista MiniTest
HallusionBench aAcc
LLaVA-v1.5-7B (XTuner)
67.7
69.2
61.0
59.7
28.4
1716
66.4
32.2
33.7
24.2
46.2
LLaVA-v1.5-13B (XTuner)
68.8
69.5
64.7
63.1
32.9
1766
67.9
35.9
35.2
26.2
46.9
LLaVA-InternLM-7B (XTuner)
69.0
68.5
66.7
63.8
37.3
1637
65.7
32.4
36.9
26.3
49.1
LLaVA-InternLM2-7B
73.3
74.6
71.7
72.0
42.5
1700
71.2
35.9
40.1
25.5
46.8
LLaVA-InternLM2-20B
75.1
73.5
73.7
72.8
46.3
1868
70.2
37.2
39.4
24.6
47.7
Quickstart
Installation
pip install -U 'xtuner[deepspeed]'
Chat
xtuner chat internlm/internlm2-chat-7b \
--visual-encoder openai/clip-vit-large-patch14-336…
GLPN fine-tuned on KITTI
Global-Local Path Networks (GLPN) model trained on KITTI for monocular depth estimation. It was introduced in the paper Global-Local Path Networks for Monocular Depth Estimation with Vertical CutDepth by Kim et al. and first released in this repository.
Disclaimer: The team releasing GLPN did not write a model card…
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ppo Agent playing SnowballTarget
Usage (with ML-Agents)
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ppo Agent playing SnowballTarget
This is a trained model of a ppo agent playing SnowballTarget
using the Unity ML-Agents Library.
Usage (with ML-Agents)
The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/
We…
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Model Description
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