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  - en
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  base_model:
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  - HuggingFaceTB/SmolLM2-1.7B-Instruct
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- pipeline_tag: question-answering
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  ---
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- # Model Card for Model ID
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- Kurtis is a fine-tuning, inference and evaluation tool built for SLMs (Small Language Models) such as Huggingface's SmolLM2.
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  ## Model Details
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  ### Model Description
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  - **Developed by:** Massimo R. Scamarcia <[email protected]>
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- - **Funded by [optional]:** Massimo R. Scamarcia <[email protected]> - (self-funded)
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- - **Shared by [optional]:** Massimo R. Scamarcia <[email protected]>
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  - **Model type:** Transformer decoder
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  - **Language(s) (NLP):** English
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  - **License:** MIT
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- - **Finetuned from model [optional]:** HuggingFaceTB/SmolLM2-1.7B-Instruct
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- ### Model Sources [optional]
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- <!-- Provide the basic links for the model. -->
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  - **Repository:** [https://github.com/mrs83/kurtis](https://github.com/mrs83/kurtis)
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- - **Paper [optional]:** None
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- - **Demo [optional]:** [More Information Needed]
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  ## Uses
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- The model is intended for use in a conversational setting, particularly in mental health and therapeutic support scenarios.
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- Suitable use cases include:
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- - Evaluating the usage of small-language models (SLMs).
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- - Evaluating small-language models (SLMs) capability to generate empathetic responses in a mental-health context.
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  ### Direct Use
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  Not suitable for production usage.
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  ### Out-of-Scope Use
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  This model should not be used for:
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  - Applications where responses require regulatory compliance or are highly sensitive.
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  - Generating responses without human supervision, especially in contexts that involve vulnerable individuals.
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-
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  ## Bias, Risks, and Limitations
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  Misuse of this dataset could lead to providing inappropriate or harmful responses, so it should not be deployed without proper safeguards in place.
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  ### Recommendations
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- Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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  ## How to Get Started with the Model
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- Use the code below to get started with the model.
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- [More Information Needed]
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- ## Training Details
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- ### Training Data
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- WIP
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- [More Information Needed]
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- ### Training Procedure
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- <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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- #### Preprocessing [optional]
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- [More Information Needed]
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- #### Training Hyperparameters
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- - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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- #### Speeds, Sizes, Times [optional]
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- <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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- [More Information Needed]
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- ## Evaluation
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- <!-- This section describes the evaluation protocols and provides the results. -->
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- ### Testing Data, Factors & Metrics
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- #### Testing Data
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- <!-- This should link to a Dataset Card if possible. -->
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- [More Information Needed]
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- #### Factors
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- <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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- [More Information Needed]
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- #### Metrics
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- <!-- These are the evaluation metrics being used, ideally with a description of why. -->
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- [More Information Needed]
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- ### Results
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- [More Information Needed]
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- #### Summary
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- ## Technical Specifications [optional]
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- ### Model Architecture and Objective
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- [More Information Needed]
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- ### Compute Infrastructure
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- [More Information Needed]
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- #### Hardware
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- [More Information Needed]
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- #### Software
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- [More Information Needed]
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- ## Model Card Contact
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- Massimo R. Scamarcia <[email protected]>
 
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  - en
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  base_model:
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  - HuggingFaceTB/SmolLM2-1.7B-Instruct
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+ pipeline_tag: text-generation
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  ---
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+ # Model Card for Kurtis-SmolLM2-1.7B-Instruct
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+ This model has been fine-tuned using Kurtis, an experimental fine-tuning, inference and evaluation tool for Small Language Models.
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  ## Model Details
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  ### Model Description
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  - **Developed by:** Massimo R. Scamarcia <[email protected]>
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+ - **Funded by:** Massimo R. Scamarcia <[email protected]> - (self-funded)
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+ - **Shared by:** Massimo R. Scamarcia <[email protected]>
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  - **Model type:** Transformer decoder
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  - **Language(s) (NLP):** English
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  - **License:** MIT
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+ - **Finetuned from model:** HuggingFaceTB/SmolLM2-1.7B-Instruct
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+ ### Model Sources
 
 
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  - **Repository:** [https://github.com/mrs83/kurtis](https://github.com/mrs83/kurtis)
 
 
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  ## Uses
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+ The model is intended for use in a conversational setting, particularly in mental health and therapeutic support scenarios.
 
 
 
 
 
 
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  ### Direct Use
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  Not suitable for production usage.
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  ### Out-of-Scope Use
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  This model should not be used for:
 
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  - Applications where responses require regulatory compliance or are highly sensitive.
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  - Generating responses without human supervision, especially in contexts that involve vulnerable individuals.
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  ## Bias, Risks, and Limitations
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  Misuse of this dataset could lead to providing inappropriate or harmful responses, so it should not be deployed without proper safeguards in place.
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  ### Recommendations
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+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model.
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  ## How to Get Started with the Model
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+ WIP