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Llama-Guard-3-1B-Q4_K_M

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jquirion commited on Oct 18

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 # Model Card for Model ID
-<!-- Provide a quick summary of what the model is/does. -->
-This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).
-## Model Details
 ### Model Description
-<!-- Provide a longer summary of what this model is. -->
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
-### Model Sources [optional]
-<!-- Provide the basic links for the model. -->
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-## Uses
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-### Direct Use
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-### Downstream Use [optional]
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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-### Out-of-Scope Use
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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-## Bias, Risks, and Limitations
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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-### Recommendations
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
-## How to Get Started with the Model
-Use the code below to get started with the model.
-[More Information Needed]
-## Training Details
-### Training Data
-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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-### Training Procedure
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
-#### Preprocessing [optional]
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-#### Training Hyperparameters
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-#### Speeds, Sizes, Times [optional]
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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-## Evaluation
-<!-- This section describes the evaluation protocols and provides the results. -->
-### Testing Data, Factors & Metrics
-#### Testing Data
-<!-- This should link to a Dataset Card if possible. -->
-[More Information Needed]
-#### Factors
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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-#### Metrics
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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-### Results
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-#### Summary
-## Model Examination [optional]
-<!-- Relevant interpretability work for the model goes here -->
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-## Environmental Impact
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-## Technical Specifications [optional]
-### Model Architecture and Objective
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-### Compute Infrastructure
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-#### Hardware
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-#### Software
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-## Citation [optional]
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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-## Glossary [optional]
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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-## More Information [optional]
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-## Model Card Authors [optional]
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-## Model Card Contact
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 ---
 # Model Card for Model ID
+This model is a Q4_K_M quantized version of meta-llama/Llama-Gard-3-1B and is provided in GGUF file format.
+It is intended for fast execution at the edge using llama.cpp or ollama.
+### Model Details
+1B parameters
+955.4 MB size
+Q4_K_M quantization
 ### Model Description
+This model is a Q4_K_M quantized version of meta-llama/Llama-Gard-3-1B and is provided in GGUF file format.
+It is intended for fast execution at the edge using llama.cpp or ollama.
+Runing using ollama: ollama run hf.co/jquirion/Llama-Guard-3-1B-Q4_K_M
+- **Developed by:** jquirion
+- **Model type:** Large Language Model
+- **Language(s) (NLP):** Same as Lama-Guard-3-1B
+- **License:** llama3.2
+- **Finetuned from model [optional]:** Not finetunned. Same as Lama-Guard-3-1B.
+### Use
+The model predicts safety labels on the 13 categories shown below, based on the MLCommons taxonomy of 13 hazards.
+Hazard categories:
+S1: Violent Crimes
+S2: Non-Violent Crimes
+S3: Sex-Related Crimes
+S4: Child Sexual Exploitation
+S5: Defamation
+S6: Specialized Advice
+S7: Privacy
+S8: Intellectual Property
+S9: Indiscriminate Weapons
+S10: Hate
+S11: Suicide & Self-Harm
+S12: Sexual Content
+S13: Elections