Fix some typos (#10175)

* add llm-ppl workflow * update the DATASET_DIR * test multiple precisions * modify nightly test * match the updated ppl code * add matrix.include * fix the include error * update the include * add more model * update the precision of include * update nightly time and add more models * fix the workflow_dispatch description, change default model of pr and modify the env * modify workflow_dispatch language options * modify options * modify language options * modeify workflow_dispatch type * modify type * modify the type of language * change seq_len type * fix some typos * revert changes to stress_test.txt
intel-analytics · Feb 20, 2024 · 6e10d98 · 6e10d98
1 parent add3899
commit 6e10d98
Show file tree

Hide file tree

Showing 6 changed files with 20 additions and 20 deletions.
diff --git a/.github/workflows/llm-c-evaluation.yml b/.github/workflows/llm-c-evaluation.yml
@@ -79,7 +79,7 @@ jobs:
             echo "model_name=$model_name" >> $GITHUB_OUTPUT
             echo "precision=$precision" >> $GITHUB_OUTPUT
             echo "runner=$runner" >> $GITHUB_OUTPUT
-  llm-ceval-evalution:
+  llm-ceval-evaluation:
     timeout-minutes: 1200
     needs: [llm-cpp-build, set-matrix]
     strategy:
@@ -175,7 +175,7 @@ jobs:
 
   llm-ceval-summary:
     if: ${{ always() }}
-    needs: llm-ceval-evalution
+    needs: llm-ceval-evaluation
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v3

diff --git a/.github/workflows/llm-harness-evaluation.yml b/.github/workflows/llm-harness-evaluation.yml
@@ -1,4 +1,4 @@
-name: LLM Harness Evalution
+name: LLM Harness Evaluation
 
 # Cancel previous runs in the PR when you push new commits
 concurrency:
@@ -20,19 +20,19 @@ on:
   workflow_dispatch:
     inputs:
       model_name:
-        description: 'Model names, seperated by comma and must be quoted.'
+        description: 'Model names, separated by comma and must be quoted.'
         required: true
         type: string
       precision:
-        description: 'Precisions, seperated by comma and must be quoted.'
+        description: 'Precisions, separated by comma and must be quoted.'
         required: true
         type: string
       task:
-        description: 'Tasks, seperated by comma and must be quoted.'
+        description: 'Tasks, separated by comma and must be quoted.'
         required: true
         type: string
       runs-on:
-        description: 'Labels to filter the runners, seperated by comma and must be quoted.'
+        description: 'Labels to filter the runners, separated by comma and must be quoted.'
         default: "accuracy"
         required: false
         type: string
@@ -97,7 +97,7 @@ jobs:
             echo "precision=$precision" >> $GITHUB_OUTPUT
             echo "task=$task" >> $GITHUB_OUTPUT
             echo "runner=$runner" >> $GITHUB_OUTPUT
-  llm-harness-evalution:
+  llm-harness-evaluation:
     timeout-minutes: 1000
     needs: [llm-cpp-build, set-matrix]
     strategy:
@@ -201,7 +201,7 @@ jobs:
 
   llm-harness-summary:
     if: ${{ always() }}
-    needs: llm-harness-evalution
+    needs: llm-harness-evaluation
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@f43a0e5ff2bd294095638e18286ca9a3d1956744 # actions/checkout@v3
@@ -228,7 +228,7 @@ jobs:
   # TODO: change machine to store the results later        
   llm-harness-summary-nightly:
     if: ${{github.event_name == 'schedule' || github.event_name == 'pull_request'}}
-    needs: [set-matrix, llm-harness-evalution]
+    needs: [set-matrix, llm-harness-evaluation]
     runs-on: ["self-hosted", "llm", "accuracy1", "accuracy-nightly"]
     steps:
       - uses: actions/checkout@f43a0e5ff2bd294095638e18286ca9a3d1956744 # actions/checkout@v3

diff --git a/.github/workflows/llm-ppl-evaluation.yml b/.github/workflows/llm-ppl-evaluation.yml
@@ -1,4 +1,4 @@
-name: LLM Perplexity Evalution
+name: LLM Perplexity Evaluation
 
 # Cancel previous runs in the PR when you push new commits
 concurrency:
@@ -24,19 +24,19 @@ on:
         required: true
         type: string      
       model_name:
-        description: 'Model names, seperated by comma and must be quoted.'
+        description: 'Model names, separated by comma and must be quoted.'
         required: true
         type: string
       precision:
-        description: 'Precisions, seperated by comma and must be quoted.'
+        description: 'Precisions, separated by comma and must be quoted.'
         required: true
         type: string
       language:
         description: 'language, can be en, zh, or all and must be quoted.'
         required: true
         type: string
       runs-on:
-        description: 'Labels to filter the runners, seperated by comma and must be quoted.'
+        description: 'Labels to filter the runners, separated by comma and must be quoted.'
         default: "accuracy"
         required: false
         type: string
@@ -107,7 +107,7 @@ jobs:
             echo "precision=$precision" >> $GITHUB_OUTPUT
             echo "language=$language" >> $GITHUB_OUTPUT
             echo "runner=$runner" >> $GITHUB_OUTPUT
-  llm-ppl-evalution:
+  llm-ppl-evaluation:
     timeout-minutes: 1000
     needs: [llm-cpp-build, set-matrix]
     strategy:

diff --git a/docs/readthedocs/source/doc/Chronos/Overview/simulation.md b/docs/readthedocs/source/doc/Chronos/Overview/simulation.md
@@ -8,7 +8,7 @@ Chronos provides simulators to generate synthetic time series data for users who
 ```
 
 ## 1. DPGANSimulator
-`DPGANSimulator` adopt DoppelGANger raised in [Using GANs for Sharing Networked Time Series Data: Challenges, Initial Promise, and Open Questions](http://arxiv.org/abs/1909.13403). The method is data-driven unsupervised method based on deep learning model with GAN (Generative Adversarial Networks) structure. The model features a pair of seperate attribute generator and feature generator and their corresponding discriminators `DPGANSimulator` also supports a rich and comprehensive input data (training data) format and outperform other algorithms in many evalution metrics.
+`DPGANSimulator` adopt DoppelGANger raised in [Using GANs for Sharing Networked Time Series Data: Challenges, Initial Promise, and Open Questions](http://arxiv.org/abs/1909.13403). The method is data-driven unsupervised method based on deep learning model with GAN (Generative Adversarial Networks) structure. The model features a pair of separate attribute generator and feature generator and their corresponding discriminators `DPGANSimulator` also supports a rich and comprehensive input data (training data) format and outperform other algorithms in many evaluation metrics.
 
 ```eval_rst
 .. note::

diff --git a/docs/readthedocs/source/doc/Chronos/QuickStart/index.md b/docs/readthedocs/source/doc/Chronos/QuickStart/index.md
@@ -281,7 +281,7 @@
                 </p>
             </summary>
             <img src="../../../_images/GitHub-Mark-32px.png"><a href="https://github.com/intel-analytics/BigDL/tree/main/python/chronos/example/onnx">View source on GitHub</a>
-            <p>This example will demonstrate how to use ONNX to speed up the inferencing(prediction/evalution) on forecasters and AutoTSEstimator. In this example, onnx speed up the inferencing for ~4X.</p>
+            <p>This example will demonstrate how to use ONNX to speed up the inferencing(prediction/evaluation) on forecasters and AutoTSEstimator. In this example, onnx speed up the inferencing for ~4X.</p>
         </details>
         <hr>
 

diff --git a/python/llm/dev/benchmark/harness/README.md b/python/llm/dev/benchmark/harness/README.md
@@ -1,5 +1,5 @@
-# Harness Evalution
-[Harness evalution](https://github.com/EleutherAI/lm-evaluation-harness) allows users to eaisly get accuracy on various datasets. Here we have enabled harness evalution with BigDL-LLM under 
+# Harness Evaluation
+[Harness evaluation](https://github.com/EleutherAI/lm-evaluation-harness) allows users to eaisly get accuracy on various datasets. Here we have enabled harness evaluation with BigDL-LLM under 
 [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) settings.
 Before running, make sure to have [bigdl-llm](../../../README.md) installed.
 
@@ -12,7 +12,7 @@ pip install -e .
 ```
 
 ## Run
-run `python run_llb.py`. `run_llb.py` combines some arguments in `main.py` to make evalutions easier. The mapping of arguments is defined as a dict in [`llb.py`](llb.py).
+run `python run_llb.py`. `run_llb.py` combines some arguments in `main.py` to make evaluations easier. The mapping of arguments is defined as a dict in [`llb.py`](llb.py).
 
 ### Evaluation on CPU
 ```python