Hellisotherpeople
commited on
Commit
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d0947a0
1
Parent(s):
54bc823
Update Objects.py
Browse files- Objects.py +11 -12
Objects.py
CHANGED
@@ -19,10 +19,9 @@ st.set_page_config(page_title="Oracle")
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image = Image.open('oracle_huggingface.png')
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st.image(image)
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st.title("Oracle x HF
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st.
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st.caption("The first of many features and integrations between HF and OCI")
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st.caption("After the OCI Object Storage Upload Functionality is finished, next step is to make HF models deployable on OCI")
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config_location = ".oci/config"
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@@ -39,10 +38,10 @@ hf_dataset = ""
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oracle_form = st.form("configuration")
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oracle_form.write("OCI Settings")
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user_ocid = oracle_form.text_input("Enter the User OCID", "
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tenancy_ocid = oracle_form.text_input("Enter the tenancy ocid", "
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region = oracle_form.text_input("Enter the region", "us-ashburn-1")
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existing_checkbox = oracle_form.checkbox("Check this if you want to put the dataset into an existing bucket")
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@@ -52,11 +51,11 @@ oracle_submitted = oracle_form.form_submit_button("Generate API Key")
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dataset_form = st.form("dataset")
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dataset_form.write("Dataset Settings")
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dataset_name = dataset_form.text_area("Enter the name of the huggingface Dataset:", value = "biosses")
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dataset_name_2 = dataset_form.text_area("Enter the name of the config for the dataset if it has one", value = " ")
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split_name = dataset_form.text_area("Enter the name of the split of the dataset that you want to use", value = "train")
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pd_checkbox = dataset_form.checkbox("Check this if you want this to be a pandas dataframe instead of a HF Dataset Object")
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dataset_submitted = dataset_form.form_submit_button("
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def load_and_process_data(path, name, streaming, split_name):
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@@ -140,7 +139,7 @@ if dataset_submitted:
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bucket_name,
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bucket_name,
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hf_bytes)
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st.write("Object
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image = Image.open('oracle_huggingface.png')
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st.image(image)
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st.title("Oracle x HF")
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st.header("Upload HF Dataset to OCI Object Storage!")
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st.caption("The first of many features and integrations between HF and OCI")
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config_location = ".oci/config"
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oracle_form = st.form("configuration")
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oracle_form.write("OCI Settings")
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user_ocid = oracle_form.text_input("Enter the User OCID", help="To find your user OCID, first login to your OCI account. From the home screen, click on the top right face icon marked as profile and click on your email. From here, find and copy your OCID into this box")
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tenancy_ocid = oracle_form.text_input("Enter the tenancy ocid", help="To find your user OCID, first login to your OCI account. From the home screen, click on the top right face icon marked as profile and click on your tenancy. From here, find and copy your OCID into this box")
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region = oracle_form.text_input("Enter the region", "us-ashburn-1" help="To find your region identifier, first login to your OCI account. From the home screen, click on the top right region name. Scroll to the bottom of the regions list to the option labeled as manage region. Within this, the list of region identifiers is available. Copy your corresponding region identifier into here.")
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existing_checkbox = oracle_form.checkbox("Check this if you want to put the dataset into an existing bucket rather than create a new one")
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dataset_form = st.form("dataset")
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dataset_form.write("Dataset Settings")
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dataset_name = dataset_form.text_area("Enter the name of the huggingface Dataset:", value = "biosses", help ="Datasets can be found here: https://huggingface.co/datasets The default, BIOSSES is a benchmark dataset for biomedical sentence similarity estimation.")
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dataset_name_2 = dataset_form.text_area("Enter the name of the config for the dataset if it has one", value = " ", help="Some datasets have config options associated with them, enter them here")
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split_name = dataset_form.text_area("Enter the name of the split of the dataset that you want to use", value = "train")
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pd_checkbox = dataset_form.checkbox("Check this if you want this to be uploaded as a pandas dataframe instead of a HF Dataset Object")
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dataset_submitted = dataset_form.form_submit_button("Upload Dataset to OCI Object Storage")
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def load_and_process_data(path, name, streaming, split_name):
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bucket_name,
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bucket_name,
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hf_bytes)
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st.write("Object Uploaded Successfully!")
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