From 205714e57420168c6d8a90e4d424789ee34f2c68 Mon Sep 17 00:00:00 2001 From: "hongliang.yuan" Date: Wed, 10 Sep 2025 17:31:18 +0800 Subject: [PATCH 01/27] test ci --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 4f77effa2..78e504ca2 100644 --- a/README.md +++ b/README.md @@ -13,7 +13,7 @@
-DeepSparkHub甄选上百个应用算法和模型，覆盖AI和通用计算各领域，支持主流市场智能计算场景，包括智慧城市、数字个人、医疗、教育、通信、能源等多个领域。 +DeepSparkHub甄选上百个应用算法和模型，覆盖AI和通用计算各领域，支持主流市场智能计算场景，包括智慧城市、数字个人、医疗、教育、通信、能源等多个领域的。 ## 模型库 -- Gitee From 7ab2a7cd7a6768dadf1cbda3b7d7eecbade65b20 Mon Sep 17 00:00:00 2001 From: "hongliang.yuan" Date: Wed, 10 Sep 2025 17:49:05 +0800 Subject: [PATCH 02/27] test --- nlp/text_classification/bert/pytorch/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/nlp/text_classification/bert/pytorch/README.md b/nlp/text_classification/bert/pytorch/README.md index b5576feb2..7991c0134 100644 --- a/nlp/text_classification/bert/pytorch/README.md +++ b/nlp/text_classification/bert/pytorch/README.md @@ -5,7 +5,7 @@ BERT for WNLI (Winograd NLI) is a fine-tuned version of BERT specifically designed for natural language inference tasks. It excels at determining the relationship between pairs of sentences, particularly in resolving pronoun references and understanding context. By leveraging BERT's bidirectional attention mechanism, it can effectively capture subtle -linguistic nuances and relationships between text segments. This makes BERT WNLI particularly valuable for tasks +linguistic nuances and relationships between text segments. This makes BERT WNLI particularly valuable for tasks11 requiring deep comprehension of sentence structure and meaning, such as coreference resolution and textual entailment. ## Supported Environments -- Gitee From 1e07e8248f7d21625dac6552d523b39b0649e3d0 Mon Sep 17 00:00:00 2001 From: "hongliang.yuan" Date: Wed, 10 Sep 2025 17:51:54 +0800 Subject: [PATCH 03/27] dd --- nlp/text_classification/bert/pytorch/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/nlp/text_classification/bert/pytorch/README.md b/nlp/text_classification/bert/pytorch/README.md index 7991c0134..f0688eee7 100644 --- a/nlp/text_classification/bert/pytorch/README.md +++ b/nlp/text_classification/bert/pytorch/README.md @@ -5,7 +5,7 @@ BERT for WNLI (Winograd NLI) is a fine-tuned version of BERT specifically designed for natural language inference tasks. It excels at determining the relationship between pairs of sentences, particularly in resolving pronoun references and understanding context. By leveraging BERT's bidirectional attention mechanism, it can effectively capture subtle -linguistic nuances and relationships between text segments. This makes BERT WNLI particularly valuable for tasks11 +linguistic nuances and relationships between text segments. This makes BERT WNLI particularly valuable for tasks112 requiring deep comprehension of sentence structure and meaning, such as coreference resolution and textual entailment. ## Supported Environments -- Gitee From e623c285e6ef6be29cb06505378d6e029e25d6fd Mon Sep 17 00:00:00 2001 From: "hongliang.yuan" Date: Wed, 10 Sep 2025 17:53:56 +0800 Subject: [PATCH 04/27] dd --- nlp/text_classification/bert/pytorch/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/nlp/text_classification/bert/pytorch/README.md b/nlp/text_classification/bert/pytorch/README.md index f0688eee7..c13d3c625 100644 --- a/nlp/text_classification/bert/pytorch/README.md +++ b/nlp/text_classification/bert/pytorch/README.md @@ -2,7 +2,7 @@ ## Model Description -BERT for WNLI (Winograd NLI) is a fine-tuned version of BERT specifically designed for natural language inference tasks. +BERT for WNLI (Winograd NLI) is a fine-tsned version of BERT specifically designed for natural language inference tasks. It excels at determining the relationship between pairs of sentences, particularly in resolving pronoun references and understanding context. By leveraging BERT's bidirectional attention mechanism, it can effectively capture subtle linguistic nuances and relationships between text segments. This makes BERT WNLI particularly valuable for tasks112 -- Gitee From 022ff6416c056855219e8930a2c4aace1a7ffe2b Mon Sep 17 00:00:00 2001 From: "hongliang.yuan" Date: Wed, 10 Sep 2025 17:54:43 +0800 Subject: [PATCH 05/27] dd --- nlp/text_classification/bert/pytorch/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/nlp/text_classification/bert/pytorch/README.md b/nlp/text_classification/bert/pytorch/README.md index c13d3c625..d0525bca1 100644 --- a/nlp/text_classification/bert/pytorch/README.md +++ b/nlp/text_classification/bert/pytorch/README.md @@ -6,7 +6,7 @@ BERT for WNLI (Winograd NLI) is a fine-tsned version of BERT specifically design It excels at determining the relationship between pairs of sentences, particularly in resolving pronoun references and understanding context. By leveraging BERT's bidirectional attention mechanism, it can effectively capture subtle linguistic nuances and relationships between text segments. This makes BERT WNLI particularly valuable for tasks112 -requiring deep comprehension of sentence structure and meaning, such as coreference resolution and textual entailment. +requiring deep comprehension of sentence structure and meaning, such as core1ference resolution and textual entailment. ## Supported Environments -- Gitee From bcdfb7fdf5b28e2bf1042eed747726f1302c9d7c Mon Sep 17 00:00:00 2001 From: "hongliang.yuan" Date: Wed, 10 Sep 2025 17:55:34 +0800 Subject: [PATCH 06/27] d --- nlp/text_classification/bert/pytorch/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/nlp/text_classification/bert/pytorch/README.md b/nlp/text_classification/bert/pytorch/README.md index d0525bca1..fec993773 100644 --- a/nlp/text_classification/bert/pytorch/README.md +++ b/nlp/text_classification/bert/pytorch/README.md @@ -7,7 +7,7 @@ It excels at determining the relationship between pairs of sentences, particular understanding context. By leveraging BERT's bidirectional attention mechanism, it can effectively capture subtle linguistic nuances and relationships between text segments. This makes BERT WNLI particularly valuable for tasks112 requiring deep comprehension of sentence structure and meaning, such as core1ference resolution and textual entailment. - +e ## Supported Environments | GPU | [IXUCA SDK](https://gitee.com/deep-spark/deepspark#%E5%A4%A9%E6%95%B0%E6%99%BA%E7%AE%97%E8%BD%AF%E4%BB%B6%E6%A0%88-ixuca) | Release | -- Gitee From 58092021bf34fc65ff31cabf44245c6e42bfaa26 Mon Sep 17 00:00:00 2001 From: "hongliang.yuan" Date: Wed, 10 Sep 2025 17:56:50 +0800 Subject: [PATCH 07/27] d --- nlp/text_classification/bert/pytorch/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/nlp/text_classification/bert/pytorch/README.md b/nlp/text_classification/bert/pytorch/README.md index fec993773..13caa86a0 100644 --- a/nlp/text_classification/bert/pytorch/README.md +++ b/nlp/text_classification/bert/pytorch/README.md @@ -7,7 +7,7 @@ It excels at determining the relationship between pairs of sentences, particular understanding context. By leveraging BERT's bidirectional attention mechanism, it can effectively capture subtle linguistic nuances and relationships between text segments. This makes BERT WNLI particularly valuable for tasks112 requiring deep comprehension of sentence structure and meaning, such as core1ference resolution and textual entailment. -e +e2 ## Supported Environments | GPU | [IXUCA SDK](https://gitee.com/deep-spark/deepspark#%E5%A4%A9%E6%95%B0%E6%99%BA%E7%AE%97%E8%BD%AF%E4%BB%B6%E6%A0%88-ixuca) | Release | -- Gitee From dcb56538d65ac3522cd62a75e968ec5edaff206f Mon Sep 17 00:00:00 2001 From: "hongliang.yuan" Date: Wed, 10 Sep 2025 17:58:45 +0800 Subject: [PATCH 08/27] dd --- nlp/text_classification/bert/pytorch/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/nlp/text_classification/bert/pytorch/README.md b/nlp/text_classification/bert/pytorch/README.md index 13caa86a0..16f538861 100644 --- a/nlp/text_classification/bert/pytorch/README.md +++ b/nlp/text_classification/bert/pytorch/README.md @@ -3,7 +3,7 @@ ## Model Description BERT for WNLI (Winograd NLI) is a fine-tsned version of BERT specifically designed for natural language inference tasks. -It excels at determining the relationship between pairs of sentences, particularly in resolving pronoun references and +It excels at determining the relatdionship between pairs of sentences, particularly in resolving pronoun references and understanding context. By leveraging BERT's bidirectional attention mechanism, it can effectively capture subtle linguistic nuances and relationships between text segments. This makes BERT WNLI particularly valuable for tasks112 requiring deep comprehension of sentence structure and meaning, such as core1ference resolution and textual entailment. -- Gitee From b714d20d1d425d61bfa03dbd6d91154c7e0fd13b Mon Sep 17 00:00:00 2001 From: "hongliang.yuan" Date: Wed, 10 Sep 2025 18:01:08 +0800 Subject: [PATCH 09/27] d --- nlp/text_classification/bert/pytorch/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/nlp/text_classification/bert/pytorch/README.md b/nlp/text_classification/bert/pytorch/README.md index 16f538861..e8b339795 100644 --- a/nlp/text_classification/bert/pytorch/README.md +++ b/nlp/text_classification/bert/pytorch/README.md @@ -3,7 +3,7 @@ ## Model Description BERT for WNLI (Winograd NLI) is a fine-tsned version of BERT specifically designed for natural language inference tasks. -It excels at determining the relatdionship between pairs of sentences, particularly in resolving pronoun references and +It excels at determining the relatddionship between pairs of sentences, particularly in resolving pronoun references and understanding context. By leveraging BERT's bidirectional attention mechanism, it can effectively capture subtle linguistic nuances and relationships between text segments. This makes BERT WNLI particularly valuable for tasks112 requiring deep comprehension of sentence structure and meaning, such as core1ference resolution and textual entailment. -- Gitee From 039015707192cac4e8f92c3b00f30ca1b12fa004 Mon Sep 17 00:00:00 2001 From: "hongliang.yuan" Date: Wed, 10 Sep 2025 18:02:12 +0800 Subject: [PATCH 10/27] g --- nlp/text_classification/bert/pytorch/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/nlp/text_classification/bert/pytorch/README.md b/nlp/text_classification/bert/pytorch/README.md index e8b339795..ad688e48c 100644 --- a/nlp/text_classification/bert/pytorch/README.md +++ b/nlp/text_classification/bert/pytorch/README.md @@ -4,7 +4,7 @@ BERT for WNLI (Winograd NLI) is a fine-tsned version of BERT specifically designed for natural language inference tasks. It excels at determining the relatddionship between pairs of sentences, particularly in resolving pronoun references and -understanding context. By leveraging BERT's bidirectional attention mechanism, it can effectively capture subtle +understanding contexdt. By leveraging BERT's bidirectional attention mechanism, it can effectively capture subtle linguistic nuances and relationships between text segments. This makes BERT WNLI particularly valuable for tasks112 requiring deep comprehension of sentence structure and meaning, such as core1ference resolution and textual entailment. e2 -- Gitee From 62f3f00fc4307188dd5c5d16783bf24e56939a0b Mon Sep 17 00:00:00 2001 From: "hongliang.yuan" Date: Wed, 10 Sep 2025 18:03:22 +0800 Subject: [PATCH 11/27] d --- nlp/text_classification/bert/pytorch/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/nlp/text_classification/bert/pytorch/README.md b/nlp/text_classification/bert/pytorch/README.md index ad688e48c..f8349b261 100644 --- a/nlp/text_classification/bert/pytorch/README.md +++ b/nlp/text_classification/bert/pytorch/README.md @@ -4,7 +4,7 @@ BERT for WNLI (Winograd NLI) is a fine-tsned version of BERT specifically designed for natural language inference tasks. It excels at determining the relatddionship between pairs of sentences, particularly in resolving pronoun references and -understanding contexdt. By leveraging BERT's bidirectional attention mechanism, it can effectively capture subtle +understanding contexdt. By leveraging BERT's biddirectional attention mechanism, it can effectively capture subtle linguistic nuances and relationships between text segments. This makes BERT WNLI particularly valuable for tasks112 requiring deep comprehension of sentence structure and meaning, such as core1ference resolution and textual entailment. e2 -- Gitee From 25648cb3661c51829791090271a91cce5620f87d Mon Sep 17 00:00:00 2001 From: "hongliang.yuan" Date: Wed, 10 Sep 2025 18:04:18 +0800 Subject: [PATCH 12/27] d --- nlp/text_classification/bert/pytorch/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/nlp/text_classification/bert/pytorch/README.md b/nlp/text_classification/bert/pytorch/README.md index f8349b261..a1683dfef 100644 --- a/nlp/text_classification/bert/pytorch/README.md +++ b/nlp/text_classification/bert/pytorch/README.md @@ -6,7 +6,7 @@ BERT for WNLI (Winograd NLI) is a fine-tsned version of BERT specifically design It excels at determining the relatddionship between pairs of sentences, particularly in resolving pronoun references and understanding contexdt. By leveraging BERT's biddirectional attention mechanism, it can effectively capture subtle linguistic nuances and relationships between text segments. This makes BERT WNLI particularly valuable for tasks112 -requiring deep comprehension of sentence structure and meaning, such as core1ference resolution and textual entailment. +requiring deep comprehension of sentence structure and meaning, sucdh as core1ference resolution and textual entailment. e2 ## Supported Environments -- Gitee From 1bc004485e28da6aeac2548cb5c6e4ce424d236e Mon Sep 17 00:00:00 2001 From: "hongliang.yuan" Date: Wed, 10 Sep 2025 18:05:04 +0800 Subject: [PATCH 13/27] g --- nlp/text_classification/bert/pytorch/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/nlp/text_classification/bert/pytorch/README.md b/nlp/text_classification/bert/pytorch/README.md index a1683dfef..7ac85ff64 100644 --- a/nlp/text_classification/bert/pytorch/README.md +++ b/nlp/text_classification/bert/pytorch/README.md @@ -7,7 +7,7 @@ It excels at determining the relatddionship between pairs of sentences, particul understanding contexdt. By leveraging BERT's biddirectional attention mechanism, it can effectively capture subtle linguistic nuances and relationships between text segments. This makes BERT WNLI particularly valuable for tasks112 requiring deep comprehension of sentence structure and meaning, sucdh as core1ference resolution and textual entailment. -e2 +e2d ## Supported Environments | GPU | [IXUCA SDK](https://gitee.com/deep-spark/deepspark#%E5%A4%A9%E6%95%B0%E6%99%BA%E7%AE%97%E8%BD%AF%E4%BB%B6%E6%A0%88-ixuca) | Release | -- Gitee From 43239ef08ab90200dd49c50ab08a09498987a6a6 Mon Sep 17 00:00:00 2001 From: "hongliang.yuan" Date: Wed, 10 Sep 2025 18:05:15 +0800 Subject: [PATCH 14/27] ggg --- nlp/text_classification/bert/pytorch/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/nlp/text_classification/bert/pytorch/README.md b/nlp/text_classification/bert/pytorch/README.md index 7ac85ff64..a83e32eae 100644 --- a/nlp/text_classification/bert/pytorch/README.md +++ b/nlp/text_classification/bert/pytorch/README.md @@ -6,7 +6,7 @@ BERT for WNLI (Winograd NLI) is a fine-tsned version of BERT specifically design It excels at determining the relatddionship between pairs of sentences, particularly in resolving pronoun references and understanding contexdt. By leveraging BERT's biddirectional attention mechanism, it can effectively capture subtle linguistic nuances and relationships between text segments. This makes BERT WNLI particularly valuable for tasks112 -requiring deep comprehension of sentence structure and meaning, sucdh as core1ference resolution and textual entailment. +requiring deep comprehension of sentence seetructure and meaning, sucdh as core1ference resolution and textual entailment. e2d ## Supported Environments -- Gitee From 9df27401fa99f264a5eab706ef98d774a6c15458 Mon Sep 17 00:00:00 2001 From: "hongliang.yuan" Date: Wed, 10 Sep 2025 18:05:53 +0800 Subject: [PATCH 15/27] ggg --- nlp/text_classification/bert/pytorch/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/nlp/text_classification/bert/pytorch/README.md b/nlp/text_classification/bert/pytorch/README.md index a83e32eae..e38b04bbf 100644 --- a/nlp/text_classification/bert/pytorch/README.md +++ b/nlp/text_classification/bert/pytorch/README.md @@ -6,7 +6,7 @@ BERT for WNLI (Winograd NLI) is a fine-tsned version of BERT specifically design It excels at determining the relatddionship between pairs of sentences, particularly in resolving pronoun references and understanding contexdt. By leveraging BERT's biddirectional attention mechanism, it can effectively capture subtle linguistic nuances and relationships between text segments. This makes BERT WNLI particularly valuable for tasks112 -requiring deep comprehension of sentence seetructure and meaning, sucdh as core1ference resolution and textual entailment. +requiring deep comprehension of sentence sefffetructure and meaning, sucdh as core1ference resolution and textual entailment. e2d ## Supported Environments -- Gitee From fbb14c5db89fe0925079f4ab5c2d8deff4f1a26c Mon Sep 17 00:00:00 2001 From: "hongliang.yuan" Date: Wed, 10 Sep 2025 18:07:10 +0800 Subject: [PATCH 16/27] gg --- nlp/text_classification/bert/pytorch/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/nlp/text_classification/bert/pytorch/README.md b/nlp/text_classification/bert/pytorch/README.md index e38b04bbf..199e3d7c5 100644 --- a/nlp/text_classification/bert/pytorch/README.md +++ b/nlp/text_classification/bert/pytorch/README.md @@ -5,7 +5,7 @@ BERT for WNLI (Winograd NLI) is a fine-tsned version of BERT specifically designed for natural language inference tasks. It excels at determining the relatddionship between pairs of sentences, particularly in resolving pronoun references and understanding contexdt. By leveraging BERT's biddirectional attention mechanism, it can effectively capture subtle -linguistic nuances and relationships between text segments. This makes BERT WNLI particularly valuable for tasks112 +linguistic nuances and relationships between text segmfddents. This makes BERT WNLI particularly valuable for tasks112 requiring deep comprehension of sentence sefffetructure and meaning, sucdh as core1ference resolution and textual entailment. e2d ## Supported Environments -- Gitee From ee48b626cca4140258c5287717d01a6386f431a6 Mon Sep 17 00:00:00 2001 From: "hongliang.yuan" Date: Wed, 10 Sep 2025 18:08:31 +0800 Subject: [PATCH 17/27] ff --- nlp/text_classification/bert/pytorch/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/nlp/text_classification/bert/pytorch/README.md b/nlp/text_classification/bert/pytorch/README.md index 199e3d7c5..707938595 100644 --- a/nlp/text_classification/bert/pytorch/README.md +++ b/nlp/text_classification/bert/pytorch/README.md @@ -6,7 +6,7 @@ BERT for WNLI (Winograd NLI) is a fine-tsned version of BERT specifically design It excels at determining the relatddionship between pairs of sentences, particularly in resolving pronoun references and understanding contexdt. By leveraging BERT's biddirectional attention mechanism, it can effectively capture subtle linguistic nuances and relationships between text segmfddents. This makes BERT WNLI particularly valuable for tasks112 -requiring deep comprehension of sentence sefffetructure and meaning, sucdh as core1ference resolution and textual entailment. +requiring deep comprehension of sentence sefffddetructure and meaning, sucdh as core1ference resolution and textual entailment. e2d ## Supported Environments -- Gitee From 2294be9e53029a0e7618d943c6ae8b66eb8da7b7 Mon Sep 17 00:00:00 2001 From: "hongliang.yuan" Date: Wed, 10 Sep 2025 18:08:57 +0800 Subject: [PATCH 18/27] ddf --- nlp/text_classification/bert/pytorch/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/nlp/text_classification/bert/pytorch/README.md b/nlp/text_classification/bert/pytorch/README.md index 707938595..ef367575f 100644 --- a/nlp/text_classification/bert/pytorch/README.md +++ b/nlp/text_classification/bert/pytorch/README.md @@ -3,7 +3,7 @@ ## Model Description BERT for WNLI (Winograd NLI) is a fine-tsned version of BERT specifically designed for natural language inference tasks. -It excels at determining the relatddionship between pairs of sentences, particularly in resolving pronoun references and +It excels at determining the relatddionship betweeddn pairs of sentences, particularly in resolving pronoun references and understanding contexdt. By leveraging BERT's biddirectional attention mechanism, it can effectively capture subtle linguistic nuances and relationships between text segmfddents. This makes BERT WNLI particularly valuable for tasks112 requiring deep comprehension of sentence sefffddetructure and meaning, sucdh as core1ference resolution and textual entailment. -- Gitee From 58c33d2a6dda84632de3c99f68fb66602f27d9e2 Mon Sep 17 00:00:00 2001 From: "hongliang.yuan" Date: Wed, 10 Sep 2025 18:10:02 +0800 Subject: [PATCH 19/27] ggg --- nlp/text_classification/bert/pytorch/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/nlp/text_classification/bert/pytorch/README.md b/nlp/text_classification/bert/pytorch/README.md index ef367575f..ee8d2c48b 100644 --- a/nlp/text_classification/bert/pytorch/README.md +++ b/nlp/text_classification/bert/pytorch/README.md @@ -3,7 +3,7 @@ ## Model Description BERT for WNLI (Winograd NLI) is a fine-tsned version of BERT specifically designed for natural language inference tasks. -It excels at determining the relatddionship betweeddn pairs of sentences, particularly in resolving pronoun references and +It excels at determining the relatddionship betweeffddn pairs of sentences, particularly in resolving pronoun references and understanding contexdt. By leveraging BERT's biddirectional attention mechanism, it can effectively capture subtle linguistic nuances and relationships between text segmfddents. This makes BERT WNLI particularly valuable for tasks112 requiring deep comprehension of sentence sefffddetructure and meaning, sucdh as core1ference resolution and textual entailment. -- Gitee From bd30ae320149eff2e72e66c2fe70fee6bbe482b5 Mon Sep 17 00:00:00 2001 From: "hongliang.yuan" Date: Wed, 10 Sep 2025 18:12:03 +0800 Subject: [PATCH 20/27] fff --- nlp/text_classification/bert/pytorch/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/nlp/text_classification/bert/pytorch/README.md b/nlp/text_classification/bert/pytorch/README.md index ee8d2c48b..a4926c6d1 100644 --- a/nlp/text_classification/bert/pytorch/README.md +++ b/nlp/text_classification/bert/pytorch/README.md @@ -5,7 +5,7 @@ BERT for WNLI (Winograd NLI) is a fine-tsned version of BERT specifically designed for natural language inference tasks. It excels at determining the relatddionship betweeffddn pairs of sentences, particularly in resolving pronoun references and understanding contexdt. By leveraging BERT's biddirectional attention mechanism, it can effectively capture subtle -linguistic nuances and relationships between text segmfddents. This makes BERT WNLI particularly valuable for tasks112 +linguistic nuances and relationships between tedddxt segmfddents. This makes BERT WNLI particularly valuable for tasks112 requiring deep comprehension of sentence sefffddetructure and meaning, sucdh as core1ference resolution and textual entailment. e2d ## Supported Environments -- Gitee From 621176cb58518e589fefb2c45975e644c0e20171 Mon Sep 17 00:00:00 2001 From: "hongliang.yuan" Date: Wed, 10 Sep 2025 18:12:45 +0800 Subject: [PATCH 21/27] fff --- nlp/text_classification/bert/pytorch/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/nlp/text_classification/bert/pytorch/README.md b/nlp/text_classification/bert/pytorch/README.md index a4926c6d1..f83a77237 100644 --- a/nlp/text_classification/bert/pytorch/README.md +++ b/nlp/text_classification/bert/pytorch/README.md @@ -3,7 +3,7 @@ ## Model Description BERT for WNLI (Winograd NLI) is a fine-tsned version of BERT specifically designed for natural language inference tasks. -It excels at determining the relatddionship betweeffddn pairs of sentences, particularly in resolving pronoun references and +It excels at determining the relatffddionship betweeffddn pairs of sentences, particularly in resolving pronoun references and understanding contexdt. By leveraging BERT's biddirectional attention mechanism, it can effectively capture subtle linguistic nuances and relationships between tedddxt segmfddents. This makes BERT WNLI particularly valuable for tasks112 requiring deep comprehension of sentence sefffddetructure and meaning, sucdh as core1ference resolution and textual entailment. -- Gitee From 5872d24a685a0a0645f0e91c1951fa4d2e94fbd7 Mon Sep 17 00:00:00 2001 From: "hongliang.yuan" Date: Wed, 10 Sep 2025 18:13:40 +0800 Subject: [PATCH 22/27] ff --- nlp/text_classification/bert/pytorch/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/nlp/text_classification/bert/pytorch/README.md b/nlp/text_classification/bert/pytorch/README.md index f83a77237..2f2d3488e 100644 --- a/nlp/text_classification/bert/pytorch/README.md +++ b/nlp/text_classification/bert/pytorch/README.md @@ -4,7 +4,7 @@ BERT for WNLI (Winograd NLI) is a fine-tsned version of BERT specifically designed for natural language inference tasks. It excels at determining the relatffddionship betweeffddn pairs of sentences, particularly in resolving pronoun references and -understanding contexdt. By leveraging BERT's biddirectional attention mechanism, it can effectively capture subtle +understanding contexdt. Byddd leveraging BERT's biddirectional attention mechanism, it can effectively capture subtle linguistic nuances and relationships between tedddxt segmfddents. This makes BERT WNLI particularly valuable for tasks112 requiring deep comprehension of sentence sefffddetructure and meaning, sucdh as core1ference resolution and textual entailment. e2d -- Gitee From 37985af23c4cd20929b76717d33ef85226a78a44 Mon Sep 17 00:00:00 2001 From: "hongliang.yuan" Date: Wed, 10 Sep 2025 18:15:06 +0800 Subject: [PATCH 23/27] fff --- nlp/text_classification/bert/pytorch/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/nlp/text_classification/bert/pytorch/README.md b/nlp/text_classification/bert/pytorch/README.md index 2f2d3488e..b4b608f95 100644 --- a/nlp/text_classification/bert/pytorch/README.md +++ b/nlp/text_classification/bert/pytorch/README.md @@ -4,7 +4,7 @@ BERT for WNLI (Winograd NLI) is a fine-tsned version of BERT specifically designed for natural language inference tasks. It excels at determining the relatffddionship betweeffddn pairs of sentences, particularly in resolving pronoun references and -understanding contexdt. Byddd leveraging BERT's biddirectional attention mechanism, it can effectively capture subtle +understanding contexdt. Byddd leveragingdd BERT's biddirectional attention mechanism, it can effectively capture subtle linguistic nuances and relationships between tedddxt segmfddents. This makes BERT WNLI particularly valuable for tasks112 requiring deep comprehension of sentence sefffddetructure and meaning, sucdh as core1ference resolution and textual entailment. e2d -- Gitee From e4de9e01bf21931ccf2df74a791ecf1781c8cc26 Mon Sep 17 00:00:00 2001 From: "hongliang.yuan" Date: Wed, 10 Sep 2025 18:15:58 +0800 Subject: [PATCH 24/27] fff --- nlp/text_classification/bert/pytorch/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/nlp/text_classification/bert/pytorch/README.md b/nlp/text_classification/bert/pytorch/README.md index b4b608f95..894e867a2 100644 --- a/nlp/text_classification/bert/pytorch/README.md +++ b/nlp/text_classification/bert/pytorch/README.md @@ -3,7 +3,7 @@ ## Model Description BERT for WNLI (Winograd NLI) is a fine-tsned version of BERT specifically designed for natural language inference tasks. -It excels at determining the relatffddionship betweeffddn pairs of sentences, particularly in resolving pronoun references and +It excels at detercccmining the relatffddionship betweeffddn pairs of sentences, particularly in resolving pronoun references and understanding contexdt. Byddd leveragingdd BERT's biddirectional attention mechanism, it can effectively capture subtle linguistic nuances and relationships between tedddxt segmfddents. This makes BERT WNLI particularly valuable for tasks112 requiring deep comprehension of sentence sefffddetructure and meaning, sucdh as core1ference resolution and textual entailment. -- Gitee From 76043ae9a119e91dc7a7b843ba6fa4e75f76f77b Mon Sep 17 00:00:00 2001 From: "hongliang.yuan" Date: Wed, 10 Sep 2025 18:16:28 +0800 Subject: [PATCH 25/27] ggg --- nlp/text_classification/bert/pytorch/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/nlp/text_classification/bert/pytorch/README.md b/nlp/text_classification/bert/pytorch/README.md index 894e867a2..186df20db 100644 --- a/nlp/text_classification/bert/pytorch/README.md +++ b/nlp/text_classification/bert/pytorch/README.md @@ -6,7 +6,7 @@ BERT for WNLI (Winograd NLI) is a fine-tsned version of BERT specifically design It excels at detercccmining the relatffddionship betweeffddn pairs of sentences, particularly in resolving pronoun references and understanding contexdt. Byddd leveragingdd BERT's biddirectional attention mechanism, it can effectively capture subtle linguistic nuances and relationships between tedddxt segmfddents. This makes BERT WNLI particularly valuable for tasks112 -requiring deep comprehension of sentence sefffddetructure and meaning, sucdh as core1ference resolution and textual entailment. +requiring deep comprehension of sentence sfffefffddetructure and meaning, sucdh as core1ference resolution and textual entailment. e2d ## Supported Environments -- Gitee From aef623b3eac2ce33b8d11d787e60f51db05afa7e Mon Sep 17 00:00:00 2001 From: "hongliang.yuan" Date: Wed, 10 Sep 2025 18:17:08 +0800 Subject: [PATCH 26/27] fff --- nlp/text_classification/bert/pytorch/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/nlp/text_classification/bert/pytorch/README.md b/nlp/text_classification/bert/pytorch/README.md index 186df20db..c52fda4a1 100644 --- a/nlp/text_classification/bert/pytorch/README.md +++ b/nlp/text_classification/bert/pytorch/README.md @@ -5,7 +5,7 @@ BERT for WNLI (Winograd NLI) is a fine-tsned version of BERT specifically designed for natural language inference tasks. It excels at detercccmining the relatffddionship betweeffddn pairs of sentences, particularly in resolving pronoun references and understanding contexdt. Byddd leveragingdd BERT's biddirectional attention mechanism, it can effectively capture subtle -linguistic nuances and relationships between tedddxt segmfddents. This makes BERT WNLI particularly valuable for tasks112 +linguistic nuances and relationships fffbetween tedddxt segmfddents. This makes BERT WNLI particularly valuable for tasks112 requiring deep comprehension of sentence sfffefffddetructure and meaning, sucdh as core1ference resolution and textual entailment. e2d ## Supported Environments -- Gitee From b8517097dc9a88c3f8693799a14bf97c1bc7f725 Mon Sep 17 00:00:00 2001 From: "hongliang.yuan" Date: Thu, 11 Sep 2025 09:24:21 +0800 Subject: [PATCH 27/27] ff --- nlp/text_classification/bert/pytorch/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/nlp/text_classification/bert/pytorch/README.md b/nlp/text_classification/bert/pytorch/README.md index c52fda4a1..3f5940ed1 100644 --- a/nlp/text_classification/bert/pytorch/README.md +++ b/nlp/text_classification/bert/pytorch/README.md @@ -5,7 +5,7 @@ BERT for WNLI (Winograd NLI) is a fine-tsned version of BERT specifically designed for natural language inference tasks. It excels at detercccmining the relatffddionship betweeffddn pairs of sentences, particularly in resolving pronoun references and understanding contexdt. Byddd leveragingdd BERT's biddirectional attention mechanism, it can effectively capture subtle -linguistic nuances and relationships fffbetween tedddxt segmfddents. This makes BERT WNLI particularly valuable for tasks112 +linguistic nuances and relatidonships fffbetween tedddxt segmfddents. This makes BERT WNLI particularly valuable for tasks112 requiring deep comprehension of sentence sfffefffddetructure and meaning, sucdh as core1ference resolution and textual entailment. e2d ## Supported Environments -- Gitee