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--- |
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language: |
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- en |
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license: apache-2.0 |
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--- |
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# LLM user flow classification |
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This model identifies common events and patterns within the conversation flow. |
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Such events include, for example, complaint, when a user expresses dissatisfaction. |
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The flow labels can serve as foundational elements for sophisticated LLM analytics. |
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It is ONNX quantized and is a fined-tune of [MiniLMv2-L6-H384](https://huggingface.co/nreimers/MiniLMv2-L6-H384-distilled-from-RoBERTa-Large). |
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The base model can be found [here](https://huggingface.co/minuva/MiniLMv2-agentflow-v2) |
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This model is used *only* for the user texts. |
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For the LLM texts in the dialog use this [agent model](https://huggingface.co/minuva/MiniLMv2-agentflow-v2). |
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# Load the Model |
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```py |
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from transformers import pipeline |
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pipe = pipeline(model='minuva/MiniLMv2-userflow-v2', task='text-classification') |
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pipe("This is wrong") |
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# [{'label': 'model_wrong_or_try_again', 'score': 0.9729849100112915}] |
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``` |
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# Categories Explanation |
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<details> |
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<summary>Click to expand!</summary> |
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- OTHER: Responses that do not fit into any predefined categories or are outside the scope of the specific interaction types listed. |
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- agrees_praising_thanking: When the user agrees with the provided information, offers praise, or expresses gratitude. |
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- asks_source: The user requests the source of the information or the basis for the answer provided. |
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- continue: Indicates a prompt for the conversation to proceed or continue without a specific directional change. |
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- continue_or_finnish_code: Signals either to continue with the current line of discussion or code execution, or to conclude it. |
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- improve_or_modify_answer: The user requests an improvement or modification to the provided answer. |
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- lack_of_understandment: Reflects the user's or agent confusion or lack of understanding regarding the information provided. |
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- model_wrong_or_try_again: Indicates that the model's response was incorrect or unsatisfactory, suggesting a need to attempt another answer. |
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- more_listing_or_expand: The user requests further elaboration, expansion from the given list by the agent. |
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- repeat_answers_or_question: The need to reiterate a previous answer or question. |
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- request_example: The user asks for examples to better understand the concept or answer provided. |
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- user_complains_repetition: The user notes that the information or responses are repetitive, indicating a need for new or different content. |
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- user_doubts_answer: The user expresses skepticism or doubt regarding the accuracy or validity of the provided answer. |
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- user_goodbye: The user says goodbye to the agent. |
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- user_reminds_question: The user reiterates the question. |
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- user_wants_agent_to_answer: The user explicitly requests a response from the agent, when the agent refuses to do so. |
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- user_wants_explanation: The user seeks an explanation behind the information or answer provided. |
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- user_wants_more_detail: Indicates the user's desire for more comprehensive or detailed information on the topic. |
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- user_wants_shorter_longer_answer: The user requests that the answer be condensed or expanded to better meet their informational needs. |
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- user_wants_simplier_explanation: The user seeks a simpler, more easily understood explanation. |
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- user_wants_yes_or_no: The user is asking for a straightforward affirmative or negative answer, without additional detail or explanation. |
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</details> |
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<br> |
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# Metrics in our private test dataset |
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| Model (params) | Loss | Accuracy | F1 | |
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|--------------------|-------------|----------|--------| |
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| minuva/MiniLMv2-userflow-v2 (33M) | 0.6738 | 0.7236 | 0.7313 | |
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# Deployment |
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Check our [llm-flow-classification repository](https://github.com/minuva/llm-flow-classification) for a FastAPI and ONNX based server to deploy this model on CPU devices. |