Shikanime Deva shikanime
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shikanime
/ gh-runs-gc.nu
Last active
February 25, 2026 12:05
Garbage collect unecessary GitHub Actions runs
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| #!/usr/bin/env nu | |
| def main [user?: string, limit?: int] { | |
| let user: string = ($user | default "shikanime") | |
| let limit: int = ($limit | default 200) | |
| if (which gh | is-empty) { | |
| error make {msg: "gh CLI is not installed."} | |
| } |
shikanime
/ fix-iptable.sh
Created
February 25, 2024 12:28
Fix Kubernetes Operator Tailscale Ingress
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| # Load ip6table_filter module | |
| modprobe ip6table_filter | |
| # Persist Reboot | |
| echo ip6table_filter | sudo tee -a /etc/modules-load.d/k3s.conf |
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| #!/usr/bin/env bash | |
| SCRIPT=$(basename "$0") | |
| # fetch status | |
| STATUS=$(vcgencmd get_throttled | cut -d "=" -f 2) | |
| # decode - https://www.raspberrypi.com/documentation/computers/os.html#get_throttled | |
| echo "vcgencmd get_throttled ($STATUS)" | |
| IFS="," |
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| from operator import itemgetter | |
| from langchain.prompts.chat import ( | |
| ChatPromptTemplate, | |
| HumanMessagePromptTemplate, | |
| SystemMessagePromptTemplate, | |
| ) | |
| from langchain.chains.combine_documents import create_stuff_documents_chain | |
| from langchain_core.output_parsers import StrOutputParser | |
| from langchain.prompts.prompt import PromptTemplate |
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| spec: | |
| type: Spec | |
| documentation_url: https://docs.sonarsource.com/ | |
| connection_specification: | |
| type: object | |
| $schema: http://json-schema.org/draft-07/schema# | |
| required: | |
| - user_token | |
| - qualifiers | |
| - component_keys |
shikanime
/ settings.json
Created
October 10, 2023 20:54
VSCode VIM Settings for Colemak Users Based on jooize/vim-colemak 🤗
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| { | |
| "vim.commandLineModeKeyBindingsNonRecursive": [ | |
| { | |
| "after": ["<C-Left>"], | |
| "before": ["<C-L>"] | |
| }, | |
| { | |
| "after": ["<C-Right>"], | |
| "before": ["<C-Y>"] | |
| } |
shikanime
/ CreateModel.sql
Last active
August 31, 2023 16:24
Conducting experimentation involving similarity search through text embedding using Vertex AI. To sum up, encountering a familiar issue seen in several data products that incorporate Vertex AI—experiencing excessively high network overhead.
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| CREATE OR REPLACE MODEL | |
| search.vertex_ai_text_embeddings REMOTE | |
| WITH CONNECTION `us.vertex_ai` OPTIONS(REMOTE_SERVICE_TYPE="CLOUD_AI_TEXT_EMBEDDING_MODEL_V1") |
shikanime
/ CreateModel.sql
Last active
August 31, 2023 16:26
Exploring similarity search based on text embedding. The model, seamlessly integrated into the execution engine, offers user-friendly functionality and a performance advantage over any remote solutions.
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| CREATE OR REPLACE MODEL | |
| search.universal_sentence_encoder_large OPTIONS(model_type='tensorflow', | |
| model_path='gs://shikanime-studio-labs/universal-sentence-encoder-multilingual-large/*') |
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| FROM node:14-bullseye-slim AS runtime | |
| # Set the working directory | |
| WORKDIR /usr/src/unicorn | |
| # Define the build environment | |
| ENV NODE_ENV production | |
| # Copy the application dependencies | |
| COPY package.json yarn.lock ./ |
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| import tensorflow as tf | |
| window_size = 2 | |
| label_size = 1 | |
| inputs = tf.random.stateless_uniform(shape=(10, 3), seed=(2, 3)) | |
| dataset = tf.data.Dataset.from_tensor_slices(inputs) | |
| dataset = dataset.window(window_size + label_size, shift=label_size, drop_remainder=True) | |
| dataset = dataset.flat_map(lambda window: window.batch(window_size + label_size)) |
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