---
library_name: transformers
tags:
- nouscoder
- tools
base_model:
- NousResearch/Hermes-3-Llama-3.1-8B
license: mit
pipeline_tag: text-generation
base_model_relation: finetune
---

> [!TIP]
> **[Support this work →](https://donate.sybilsolutions.ai)** · [X](https://x.com/0xsero) · [GitHub](https://github.com/0xsero) · [REAP paper](https://arxiv.org/abs/2510.13999) · [Cerebras REAP](https://huggingface.co/collections/cerebras/cerebras-reap)

# NousCoder-14B-Tools

Tools fine-tune of [NousResearch/Hermes-3-Llama-3.1-8B](https://huggingface.co/NousResearch/Hermes-3-Llama-3.1-8B).

## At a glance

| | |
|---|---|
| Base model | [NousResearch/Hermes-3-Llama-3.1-8B](https://huggingface.co/NousResearch/Hermes-3-Llama-3.1-8B) |
| Format | Tools |
| Total params | **14B** |
| Active / token | — |
| Experts / layer | — |
| Layers | — |
| Hidden size | — |
| Context | — |
| On-disk size | 1 GB |

## Which variant should I pick?

| Variant | Format | Link |
|---|---|---|
| `NousCoder-14B-SFT` | SFT | [link](https://huggingface.co/0xSero/NousCoder-14B-SFT) |
| `NousCoder-14B-SFT-Tools` | SFT | [link](https://huggingface.co/0xSero/NousCoder-14B-SFT-Tools) |
| `NousCoder-14B-Tools` **(this)** | Tools | [link](https://huggingface.co/0xSero/NousCoder-14B-Tools) |

<!-- Provide a quick summary of what the model is/does. -->



## Model Details

### Model Description

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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

- **Developed by:** [More Information Needed]
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### Model Sources [optional]

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## Uses

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### Direct Use

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### Downstream Use [optional]

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### Out-of-Scope Use

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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.

## How to Get Started with the Model

Use the code below to get started with the model.

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## Training Details

### Training Data

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#### Preprocessing [optional]

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#### Training Hyperparameters

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#### Speeds, Sizes, Times [optional]

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## Evaluation

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#### Metrics

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### Results

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#### Summary



## Model Examination [optional]

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## Environmental Impact

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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]
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## 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]

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**BibTeX:**

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**APA:**

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## Glossary [optional]

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## Model Card Authors [optional]

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## Model Card Contact

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## License & citation
License inherited from the base model.

```bibtex
@misc{lasby2025reap,
  title  = {REAP the Experts: Why Pruning Prevails for One-Shot MoE Compression},
  author = {Mike Lasby and Ivan Lazarevich and Nish Sinnadurai and Sean Lie and Yani Ioannou and Vithursan Thangarasa},
  year   = {2025}, eprint = {2510.13999}, archivePrefix = {arXiv}
}
```

## Sponsors
Made possible by **NVIDIA · TNG Technology · Lambda · Prime Intellect · Hot Aisle**.