ayushi0430 commited on
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update readme

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  1. README.md +6 -7
  2. src/about.py +1 -1
README.md CHANGED
@@ -14,21 +14,20 @@ license: apache-2.0
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  To run this code locally:
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- 1. Change the environment variables in `src/env` and `src/about`.
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- 2. Run the following command to start the server locally:
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  ```
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- ./start.sh RUN_MODE="LOCAL" LOCAL_MODEL_NAME="<any huggingface model you want to try>"
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  Eg:
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  ./start.sh RUN_MODE="LOCAL" LOCAL_MODEL_NAME="hf-internal-testing/tiny-random-gpt2"
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  ```
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- This does not upload/download any requests/results files.
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-
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  ### Adhoc evaluation:
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- To generate result files adhoc to directly upload to results, run the following command after modifying `adhoc.py` to your needs:
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  ```
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- ./run-adhoc.sh
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  ```
 
 
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  To run this code locally:
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+ 1. Change the environment variables in `src/env` to add your API keys.
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+ 2. To run the backend server + UI locally, run the following command:
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  ```
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+ ./start.sh RUN_MODE="LOCAL" LOCAL_MODEL_NAME="<any huggingface or openai model you want to try>"
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  Eg:
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  ./start.sh RUN_MODE="LOCAL" LOCAL_MODEL_NAME="hf-internal-testing/tiny-random-gpt2"
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  ```
 
 
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  ### Adhoc evaluation:
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+ To run only the backend server locally to quickly get the evaluation results, run the following command:
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  ```
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+ ./run-adhoc.sh LOCAL_MODEL_NAME="<any huggingface or openai model you want to try>"
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  ```
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+ This will still allow you to save your benchmarking results in the folder `output-data`.
src/about.py CHANGED
@@ -175,7 +175,7 @@ f"How would you score the model's answer compared to the gold answer (using the
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  ## Reproducibility
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  1. Clone this repo by following the steps provided [here.](https://huggingface.co/spaces/lamini/leaderboard?clone=true)
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- 2. Now change the environment variables in `src/env` to add your api keys.
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  There are 2 ways to run this code locally:
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  ## Reproducibility
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  1. Clone this repo by following the steps provided [here.](https://huggingface.co/spaces/lamini/leaderboard?clone=true)
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+ 2. Now change the environment variables in `src/env` to add your API keys.
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  There are 2 ways to run this code locally:
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