---
base_model: nvidia/Llama3-ChatQA-1.5-8B
inference: false
language:
- en
library_name: gguf
license: llama3
pipeline_tag: text-generation
quantized_by: legraphista
tags:
- quantized
- GGUF
- imatrix
- quantization
- imat
- imatrix
- static
---

# Llama3-ChatQA-1.5-8B-IMat-GGUF
_Llama.cpp imatrix quantization of nvidia/Llama3-ChatQA-1.5-8B_

Original Model: [nvidia/Llama3-ChatQA-1.5-8B](https://huggingface.co/nvidia/Llama3-ChatQA-1.5-8B)  
Original dtype: `FP16` (`float16`)  
Quantized by: llama.cpp [b3003](https://github.com/ggerganov/llama.cpp/releases/tag/b3003)  
IMatrix dataset: [here](https://gist.githubusercontent.com/legraphista/d6d93f1a254bcfc58e0af3777eaec41e/raw/d380e7002cea4a51c33fffd47db851942754e7cc/imatrix.calibration.medium.raw)  

- [Llama3-ChatQA-1.5-8B-IMat-GGUF](#llama3-chatqa-1-5-8b-imat-gguf)
    - [Files](#files)
        - [IMatrix](#imatrix)
        - [Common Quants](#common-quants)
        - [All Quants](#all-quants)
    - [Downloading using huggingface-cli](#downloading-using-huggingface-cli)
    - [Inference](#inference)
        - [Simple chat template](#simple-chat-template)
        - [Llama.cpp](#llama-cpp)
    - [FAQ](#faq)
        - [Why is the IMatrix not applied everywhere?](#why-is-the-imatrix-not-applied-everywhere)
        - [How do I merge a split GGUF?](#how-do-i-merge-a-split-gguf)

---

## Files

### IMatrix
Status: ✅ Available  
Link: [here](https://huggingface.co/legraphista/Llama3-ChatQA-1.5-8B-IMat-GGUF/blob/main/imatrix.dat) 

### Common Quants
| Filename | Quant type | File Size | Status | Uses IMatrix | Is Split |
| -------- | ---------- | --------- | ------ | ------------ | -------- |
| [Llama3-ChatQA-1.5-8B.Q8_0.gguf](https://huggingface.co/legraphista/Llama3-ChatQA-1.5-8B-IMat-GGUF/blob/main/Llama3-ChatQA-1.5-8B.Q8_0.gguf) | Q8_0 | 8.54GB | ✅ Available | ⚪ No | 📦 No
| [Llama3-ChatQA-1.5-8B.Q6_K.gguf](https://huggingface.co/legraphista/Llama3-ChatQA-1.5-8B-IMat-GGUF/blob/main/Llama3-ChatQA-1.5-8B.Q6_K.gguf) | Q6_K | 6.60GB | ✅ Available | ⚪ No | 📦 No
| [Llama3-ChatQA-1.5-8B.Q4_K.gguf](https://huggingface.co/legraphista/Llama3-ChatQA-1.5-8B-IMat-GGUF/blob/main/Llama3-ChatQA-1.5-8B.Q4_K.gguf) | Q4_K | 4.92GB | ✅ Available | 🟢 Yes | 📦 No
| [Llama3-ChatQA-1.5-8B.Q3_K.gguf](https://huggingface.co/legraphista/Llama3-ChatQA-1.5-8B-IMat-GGUF/blob/main/Llama3-ChatQA-1.5-8B.Q3_K.gguf) | Q3_K | 4.02GB | ✅ Available | 🟢 Yes | 📦 No
| [Llama3-ChatQA-1.5-8B.Q2_K.gguf](https://huggingface.co/legraphista/Llama3-ChatQA-1.5-8B-IMat-GGUF/blob/main/Llama3-ChatQA-1.5-8B.Q2_K.gguf) | Q2_K | 3.18GB | ✅ Available | 🟢 Yes | 📦 No


### All Quants
| Filename | Quant type | File Size | Status | Uses IMatrix | Is Split |
| -------- | ---------- | --------- | ------ | ------------ | -------- |
| [Llama3-ChatQA-1.5-8B.FP16.gguf](https://huggingface.co/legraphista/Llama3-ChatQA-1.5-8B-IMat-GGUF/blob/main/Llama3-ChatQA-1.5-8B.FP16.gguf) | F16 | 16.07GB | ✅ Available | ⚪ No | 📦 No
| [Llama3-ChatQA-1.5-8B.Q5_K.gguf](https://huggingface.co/legraphista/Llama3-ChatQA-1.5-8B-IMat-GGUF/blob/main/Llama3-ChatQA-1.5-8B.Q5_K.gguf) | Q5_K | 5.73GB | ✅ Available | ⚪ No | 📦 No
| [Llama3-ChatQA-1.5-8B.Q5_K_S.gguf](https://huggingface.co/legraphista/Llama3-ChatQA-1.5-8B-IMat-GGUF/blob/main/Llama3-ChatQA-1.5-8B.Q5_K_S.gguf) | Q5_K_S | 5.60GB | ✅ Available | ⚪ No | 📦 No
| [Llama3-ChatQA-1.5-8B.Q4_K_S.gguf](https://huggingface.co/legraphista/Llama3-ChatQA-1.5-8B-IMat-GGUF/blob/main/Llama3-ChatQA-1.5-8B.Q4_K_S.gguf) | Q4_K_S | 4.69GB | ✅ Available | 🟢 Yes | 📦 No
| [Llama3-ChatQA-1.5-8B.Q3_K_L.gguf](https://huggingface.co/legraphista/Llama3-ChatQA-1.5-8B-IMat-GGUF/blob/main/Llama3-ChatQA-1.5-8B.Q3_K_L.gguf) | Q3_K_L | 4.32GB | ✅ Available | 🟢 Yes | 📦 No
| [Llama3-ChatQA-1.5-8B.Q3_K_S.gguf](https://huggingface.co/legraphista/Llama3-ChatQA-1.5-8B-IMat-GGUF/blob/main/Llama3-ChatQA-1.5-8B.Q3_K_S.gguf) | Q3_K_S | 3.66GB | ✅ Available | 🟢 Yes | 📦 No
| [Llama3-ChatQA-1.5-8B.Q2_K_S.gguf](https://huggingface.co/legraphista/Llama3-ChatQA-1.5-8B-IMat-GGUF/blob/main/Llama3-ChatQA-1.5-8B.Q2_K_S.gguf) | Q2_K_S | 2.99GB | ✅ Available | 🟢 Yes | 📦 No
| [Llama3-ChatQA-1.5-8B.IQ4_NL.gguf](https://huggingface.co/legraphista/Llama3-ChatQA-1.5-8B-IMat-GGUF/blob/main/Llama3-ChatQA-1.5-8B.IQ4_NL.gguf) | IQ4_NL | 4.68GB | ✅ Available | 🟢 Yes | 📦 No
| [Llama3-ChatQA-1.5-8B.IQ4_XS.gguf](https://huggingface.co/legraphista/Llama3-ChatQA-1.5-8B-IMat-GGUF/blob/main/Llama3-ChatQA-1.5-8B.IQ4_XS.gguf) | IQ4_XS | 4.45GB | ✅ Available | 🟢 Yes | 📦 No
| [Llama3-ChatQA-1.5-8B.IQ3_M.gguf](https://huggingface.co/legraphista/Llama3-ChatQA-1.5-8B-IMat-GGUF/blob/main/Llama3-ChatQA-1.5-8B.IQ3_M.gguf) | IQ3_M | 3.78GB | ✅ Available | 🟢 Yes | 📦 No
| [Llama3-ChatQA-1.5-8B.IQ3_S.gguf](https://huggingface.co/legraphista/Llama3-ChatQA-1.5-8B-IMat-GGUF/blob/main/Llama3-ChatQA-1.5-8B.IQ3_S.gguf) | IQ3_S | 3.68GB | ✅ Available | 🟢 Yes | 📦 No
| [Llama3-ChatQA-1.5-8B.IQ3_XS.gguf](https://huggingface.co/legraphista/Llama3-ChatQA-1.5-8B-IMat-GGUF/blob/main/Llama3-ChatQA-1.5-8B.IQ3_XS.gguf) | IQ3_XS | 3.52GB | ✅ Available | 🟢 Yes | 📦 No
| [Llama3-ChatQA-1.5-8B.IQ3_XXS.gguf](https://huggingface.co/legraphista/Llama3-ChatQA-1.5-8B-IMat-GGUF/blob/main/Llama3-ChatQA-1.5-8B.IQ3_XXS.gguf) | IQ3_XXS | 3.27GB | ✅ Available | 🟢 Yes | 📦 No
| [Llama3-ChatQA-1.5-8B.IQ2_M.gguf](https://huggingface.co/legraphista/Llama3-ChatQA-1.5-8B-IMat-GGUF/blob/main/Llama3-ChatQA-1.5-8B.IQ2_M.gguf) | IQ2_M | 2.95GB | ✅ Available | 🟢 Yes | 📦 No
| [Llama3-ChatQA-1.5-8B.IQ2_S.gguf](https://huggingface.co/legraphista/Llama3-ChatQA-1.5-8B-IMat-GGUF/blob/main/Llama3-ChatQA-1.5-8B.IQ2_S.gguf) | IQ2_S | 2.76GB | ✅ Available | 🟢 Yes | 📦 No
| [Llama3-ChatQA-1.5-8B.IQ2_XS.gguf](https://huggingface.co/legraphista/Llama3-ChatQA-1.5-8B-IMat-GGUF/blob/main/Llama3-ChatQA-1.5-8B.IQ2_XS.gguf) | IQ2_XS | 2.61GB | ✅ Available | 🟢 Yes | 📦 No
| [Llama3-ChatQA-1.5-8B.IQ2_XXS.gguf](https://huggingface.co/legraphista/Llama3-ChatQA-1.5-8B-IMat-GGUF/blob/main/Llama3-ChatQA-1.5-8B.IQ2_XXS.gguf) | IQ2_XXS | 2.40GB | ✅ Available | 🟢 Yes | 📦 No
| [Llama3-ChatQA-1.5-8B.IQ1_M.gguf](https://huggingface.co/legraphista/Llama3-ChatQA-1.5-8B-IMat-GGUF/blob/main/Llama3-ChatQA-1.5-8B.IQ1_M.gguf) | IQ1_M | 2.16GB | ✅ Available | 🟢 Yes | 📦 No
| [Llama3-ChatQA-1.5-8B.IQ1_S.gguf](https://huggingface.co/legraphista/Llama3-ChatQA-1.5-8B-IMat-GGUF/blob/main/Llama3-ChatQA-1.5-8B.IQ1_S.gguf) | IQ1_S | 2.02GB | ✅ Available | 🟢 Yes | 📦 No


## Downloading using huggingface-cli
If you do not have hugginface-cli installed:
```
pip install -U "huggingface_hub[cli]"
```
Download the specific file you want:
```
huggingface-cli download legraphista/Llama3-ChatQA-1.5-8B-IMat-GGUF --include "Llama3-ChatQA-1.5-8B.Q8_0.gguf" --local-dir ./
```
If the model file is big, it has been split into multiple files. In order to download them all to a local folder, run:
```
huggingface-cli download legraphista/Llama3-ChatQA-1.5-8B-IMat-GGUF --include "Llama3-ChatQA-1.5-8B.Q8_0/*" --local-dir Llama3-ChatQA-1.5-8B.Q8_0
# see FAQ for merging GGUF's
```

---

## Inference

### Simple chat template
```
<|begin_of_text|>System: This is a chat between a user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions based on the context. The assistant should also indicate when the answer cannot be found in the context.

User: Can you provide ways to eat combinations of bananas and dragonfruits?

Assistant: Sure! Here are some ways to eat bananas and dragonfruits together:
 1. Banana and dragonfruit smoothie: Blend bananas and dragonfruits together with some milk and honey.
 2. Banana and dragonfruit salad: Mix sliced bananas and dragonfruits together with some lemon juice and honey.

User: What about solving an 2x + 3 = 7 equation?

Assistant:
```

### Llama.cpp
```
llama.cpp/main -m Llama3-ChatQA-1.5-8B.Q8_0.gguf --color -i -p "prompt here (according to the chat template)"
```

---

## FAQ

### Why is the IMatrix not applied everywhere?
According to [this investigation](https://www.reddit.com/r/LocalLLaMA/comments/1993iro/ggufs_quants_can_punch_above_their_weights_now/), it appears that lower quantizations are the only ones that benefit from the imatrix input (as per hellaswag results). 

### How do I merge a split GGUF?
1. Make sure you have `gguf-split` available
    - To get hold of `gguf-split`, navigate to https://github.com/ggerganov/llama.cpp/releases
    - Download the appropriate zip for your system from the latest release
    - Unzip the archive and you should be able to find `gguf-split`
2. Locate your GGUF chunks folder (ex: `Llama3-ChatQA-1.5-8B.Q8_0`)
3. Run `gguf-split --merge Llama3-ChatQA-1.5-8B.Q8_0/Llama3-ChatQA-1.5-8B.Q8_0-00001-of-XXXXX.gguf Llama3-ChatQA-1.5-8B.Q8_0.gguf`
    - Make sure to point `gguf-split` to the first chunk of the split.

---

Got a suggestion? Ping me [@legraphista](https://x.com/legraphista)!