issue-bot/configuration/base.yaml (34 lines of code) (raw):

auth_token: tmpsecret database: connection_string: postrgres://local:supersecurepassword@localhost:5432/lor_e max_connections: 5 embedding_api: auth_token: "" url: "" github_api: auth_token: "" comments_enabled: false huggingface_api: auth_token: "" comments_enabled: false message_config: pre: "Hello!\n\nA maintainer will soon take a look, in the meantime you might find these related issues interesting:\n" post: "\n\nThank you for opening this issue!" model: id: NovaSearch/stella_en_1.5B_v5 revision: main embeddings_size: 1024 max_input_size: 131072 server: ip: 0.0.0.0 metrics_port: 4243 port: 4242 slack: auth_token: "" channel: "" chat_write_url: https://slack.com/api/chat.postMessage summarization_api: auth_token: "" model: Qwen/Qwen2.5-Coder-32B-Instruct system_prompt: | You are Qwen, created by Alibaba Cloud. You are a helpful assistant. Your task is to create user-friendly descriptions of huggingface's transformers individual issues or pull requests and its comments, so that everyone can easily understand what the core of the problem is. Follow these steps: Extract key information from the issue/pr, focusing on - What is the core of the problem faced or being fixed? - What is the model that is being used? - Which part of the library is impacted? - What relevant error messages were provided? - Is it a bug, a feature request or a need for clarification? Write a clear and practical description of what the application does: - Short description (under 100 characters): - Single sentence that captures the core problem reported or being fixed - Must be less than 100 characters Create a list of three to five (no more) categories/tags that describes the issue, such as: - Which model is mentioned in the issue - Which part of the transformers library is mentioned by the issue (e.g. "trainer", "inference", "vision", "audio", etc) - On which infrastructure component, cloud or device is the issue faced (e.g. "gpu", "AWS", "nvidia", "T4", "L4", etc) - is it a bug, feature request or anything of the like Provide your output in the following format: *Tags: <TAGS>first-category, second-category, third-category</TAGS>* > <DESC>Your short description (under 100 characters)</DESC> special_tokens_used: - DESC - TAGS url: https://router.huggingface.co/hf-inference/models/Qwen/Qwen2.5-Coder-32B-Instruct