gguf endpoints_compatible region:us conversational
---
{}
---
Quantization made by Richard Erkhov.

[Github](https://github.com/RichardErkhov)

[Discord](https://discord.gg/pvy7H8DZMG)

[Request more models](https://github.com/RichardErkhov/quant_request)


Hercules-5.0-Qwen2-1.5B - GGUF
- Model creator: https://huggingface.co/M4-ai/
- Original model: https://huggingface.co/M4-ai/Hercules-5.0-Qwen2-1.5B/


| Name | Quant method | Size |
| ---- | ---- | ---- |
| [Hercules-5.0-Qwen2-1.5B.Q2_K.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Hercules-5.0-Qwen2-1.5B-gguf/blob/main/Hercules-5.0-Qwen2-1.5B.Q2_K.gguf) | Q2_K | 0.63GB |
| [Hercules-5.0-Qwen2-1.5B.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Hercules-5.0-Qwen2-1.5B-gguf/blob/main/Hercules-5.0-Qwen2-1.5B.IQ3_XS.gguf) | IQ3_XS | 0.68GB |
| [Hercules-5.0-Qwen2-1.5B.IQ3_S.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Hercules-5.0-Qwen2-1.5B-gguf/blob/main/Hercules-5.0-Qwen2-1.5B.IQ3_S.gguf) | IQ3_S | 0.71GB |
| [Hercules-5.0-Qwen2-1.5B.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Hercules-5.0-Qwen2-1.5B-gguf/blob/main/Hercules-5.0-Qwen2-1.5B.Q3_K_S.gguf) | Q3_K_S | 0.71GB |
| [Hercules-5.0-Qwen2-1.5B.IQ3_M.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Hercules-5.0-Qwen2-1.5B-gguf/blob/main/Hercules-5.0-Qwen2-1.5B.IQ3_M.gguf) | IQ3_M | 0.72GB |
| [Hercules-5.0-Qwen2-1.5B.Q3_K.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Hercules-5.0-Qwen2-1.5B-gguf/blob/main/Hercules-5.0-Qwen2-1.5B.Q3_K.gguf) | Q3_K | 0.77GB |
| [Hercules-5.0-Qwen2-1.5B.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Hercules-5.0-Qwen2-1.5B-gguf/blob/main/Hercules-5.0-Qwen2-1.5B.Q3_K_M.gguf) | Q3_K_M | 0.77GB |
| [Hercules-5.0-Qwen2-1.5B.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Hercules-5.0-Qwen2-1.5B-gguf/blob/main/Hercules-5.0-Qwen2-1.5B.Q3_K_L.gguf) | Q3_K_L | 0.82GB |
| [Hercules-5.0-Qwen2-1.5B.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Hercules-5.0-Qwen2-1.5B-gguf/blob/main/Hercules-5.0-Qwen2-1.5B.IQ4_XS.gguf) | IQ4_XS | 0.84GB |
| [Hercules-5.0-Qwen2-1.5B.Q4_0.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Hercules-5.0-Qwen2-1.5B-gguf/blob/main/Hercules-5.0-Qwen2-1.5B.Q4_0.gguf) | Q4_0 | 0.87GB |
| [Hercules-5.0-Qwen2-1.5B.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Hercules-5.0-Qwen2-1.5B-gguf/blob/main/Hercules-5.0-Qwen2-1.5B.IQ4_NL.gguf) | IQ4_NL | 0.88GB |
| [Hercules-5.0-Qwen2-1.5B.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Hercules-5.0-Qwen2-1.5B-gguf/blob/main/Hercules-5.0-Qwen2-1.5B.Q4_K_S.gguf) | Q4_K_S | 0.88GB |
| [Hercules-5.0-Qwen2-1.5B.Q4_K.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Hercules-5.0-Qwen2-1.5B-gguf/blob/main/Hercules-5.0-Qwen2-1.5B.Q4_K.gguf) | Q4_K | 0.92GB |
| [Hercules-5.0-Qwen2-1.5B.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Hercules-5.0-Qwen2-1.5B-gguf/blob/main/Hercules-5.0-Qwen2-1.5B.Q4_K_M.gguf) | Q4_K_M | 0.92GB |
| [Hercules-5.0-Qwen2-1.5B.Q4_1.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Hercules-5.0-Qwen2-1.5B-gguf/blob/main/Hercules-5.0-Qwen2-1.5B.Q4_1.gguf) | Q4_1 | 0.95GB |
| [Hercules-5.0-Qwen2-1.5B.Q5_0.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Hercules-5.0-Qwen2-1.5B-gguf/blob/main/Hercules-5.0-Qwen2-1.5B.Q5_0.gguf) | Q5_0 | 1.02GB |
| [Hercules-5.0-Qwen2-1.5B.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Hercules-5.0-Qwen2-1.5B-gguf/blob/main/Hercules-5.0-Qwen2-1.5B.Q5_K_S.gguf) | Q5_K_S | 1.02GB |
| [Hercules-5.0-Qwen2-1.5B.Q5_K.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Hercules-5.0-Qwen2-1.5B-gguf/blob/main/Hercules-5.0-Qwen2-1.5B.Q5_K.gguf) | Q5_K | 1.05GB |
| [Hercules-5.0-Qwen2-1.5B.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Hercules-5.0-Qwen2-1.5B-gguf/blob/main/Hercules-5.0-Qwen2-1.5B.Q5_K_M.gguf) | Q5_K_M | 1.05GB |
| [Hercules-5.0-Qwen2-1.5B.Q5_1.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Hercules-5.0-Qwen2-1.5B-gguf/blob/main/Hercules-5.0-Qwen2-1.5B.Q5_1.gguf) | Q5_1 | 1.1GB |
| [Hercules-5.0-Qwen2-1.5B.Q6_K.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Hercules-5.0-Qwen2-1.5B-gguf/blob/main/Hercules-5.0-Qwen2-1.5B.Q6_K.gguf) | Q6_K | 1.19GB |
| [Hercules-5.0-Qwen2-1.5B.Q8_0.gguf](https://huggingface.co/RichardErkhov/M4-ai_-_Hercules-5.0-Qwen2-1.5B-gguf/blob/main/Hercules-5.0-Qwen2-1.5B.Q8_0.gguf) | Q8_0 | 1.53GB |




Original model description:
---
license: apache-2.0
datasets:
- Locutusque/hercules-v5.0
language:
- en
inference:
  parameters:
    do_sample: true
    temperature: 0.8
    top_p: 0.95
    top_k: 40
    min_p: 0.1
    max_new_tokens: 250
    repetition_penalty: 1.1
---


# Hercules-5.0-Qwen2-1.5B

<!-- Provide a quick summary of what the model is/does. -->
We fine-tuned qwen2-1.5B on a high quality mix for general-purpose assistants. A DPO version of this will be released soon. We use the ChatML prompt format.


## Model Details

### Model Description

<!-- Provide a longer summary of what this model is. -->

This model has capabilities in math, coding, writing, and more. We fine-tuned it using a high quality mix for general-purpose assistants.

- **Developed by:** M4-ai
- **Language(s) (NLP):** English and maybe Chinese
- **License:** apache-2.0
- **Finetuned from model:** [qwen2-1.5B](https://huggingface.co/Qwen/Qwen2-1.5B)

## 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. -->

General purpose assistant, question answering, chain-of-thought, etc..

This language model made an impressive achievement, and correctly implemented a Multi Head Attention for use in a transformer neural network.

### 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.

## Training Details

### Training Data

- Locutusque/hercules-v5.0

## Evaluations

coming soon

#### Training Hyperparameters

- **Training regime:** bf16 non-mixed precision
## Technical Specifications

#### Hardware

We used 8 Kaggle TPUs, and we trained at a global batch size of 256 and sequence length of 1536.

