Juierror
Rank:Average Model Cost: $0.0000
Number of Runs: 6,730
Models by this creator
text-to-sql-with-table-schema
text-to-sql-with-table-schema
How to use There are newer version of this using Flan-T5 as a based model. You can check out here PS. From this discussion, I think the base model that I use for finetune did not support the token <, so this might not be a good model to do this tasks.
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3.9K
Huggingface
flan-t5-text2sql-with-schema
flan-t5-text2sql-with-schema
How to use PS. From this discussion, I think the base model that I use for finetune did not support the token <, so this might not be a good model to do this tasks. However, you might consider to use work around method from vonjack.
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2.8K
Huggingface
thai-news-summarization
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16
Huggingface
whisper-base-thai
whisper-base-thai
Whisper-base Thai finetuned 1) Environment Setup 2) Usage 3) Evaluate Result This model has been trained and evaluated on three datasets: Common Voice 13 The Common Voice dataset has been cleaned and divided into training, testing, and development sets. Care has been taken to ensure that the sentences in each set are unique and do not have any duplicates. Gowajee Corpus The Gowajee dataset has already been pre-split into training, development, and testing sets, allowing for direct utilization. Thai Elderly Speech As for the Thai Elderly Speech dataset, I performed a random split. The Character Error Rate (CER) is calculated by removing spaces in both the labels and predicted text, and then computing the CER. The Word Error Rate (WER) is calculated using the PythaiNLP newmm tokenizer to tokenize both the labels and predicted text, and then computing the WER. These are the results.
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11
Huggingface
wav2vec2-large-xls-r-thai-test
wav2vec2-large-xls-r-thai-test
Platform did not provide a description for this model.
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8
Huggingface
ppo-LunarLander-v2
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0
Huggingface