---
base_model: https://huggingface.co/Phind/Phind-CodeLlama-34B-v2
inference: false
license: llama2
model_creator: https://huggingface.co/Phind
model_name: Phind-Codellama-34B-v2
model_type: llama
quantized_by: latimar
---

# Phind-CodeLlama-34B-v2 EXL2
 
Weights of [Phind-CodeLlama-34B-v2](https://huggingface.co/Phind/Phind-CodeLlama-34B-v2) converted
to [EXL2](https://github.com/turboderp/exllamav2#exl2-quantization) format.
 
Each separate quant is in a different branch, like in The Bloke's GPTQ repos.
 
```
export BRANCH=5_0-bpw-h8
git clone --single-branch --branch ${BRANCH} https://huggingface.co/latimar/Phind-Codellama-34B-v2-exl2
```
 
There are the following branches:
 
```
5_0-bpw-h8
5_0-bpw-h8-evol-ins
4_625-bpw-h6
4_125-bpw-h6
3_8-bpw-h6
2_75-bpw-h6
2_55-bpw-h6
```

* Calibration dataset used for conversion: [wikitext-v2](https://huggingface.co/datasets/wikitext/blob/refs%2Fconvert%2Fparquet/wikitext-2-v1/test/0000.parquet)
* Evaluation dataset used to calculate perplexity: [wikitext-v2](https://huggingface.co/datasets/wikitext/blob/refs%2Fconvert%2Fparquet/wikitext-2-v1/validation/0000.parquet)
* Calibration dataset used for conversion of `5_0-bpw-h8-evol-ins`: [wizardLM-evol-instruct_70k](https://huggingface.co/datasets/WizardLM/WizardLM_evol_instruct_70k/blob/refs%2Fconvert%2Fparquet/default/train/0000.parquet)
* Evaluation dataset used to calculate ppl for `Evol-Ins`: : [nikrosh-evol-instruct](https://huggingface.co/datasets/nickrosh/Evol-Instruct-Code-80k-v1/blob/refs%2Fconvert%2Fparquet/default/train/0000.parquet)
* PPL max seq. length used: 1792 (2048 with 5.0-bpw-h8 causes OOM on RTX 4090 when evaluating ppl, so had to go down a bit)
 

| BPW         | PPL on Wiki | PPL on Evol-Ins | File Size (Gb) | 
| ----------- | ----------- | --------------- | -------------- |
|  2.55-h6    |  15.0901    |                 |   10.56        |
|  2.75-h6    |  13.6153    |                 |   11.33        |
|  3.8-h6     |  6.8803     |                 |   15.37        |
|  4.125-h6   |  6.8095     |                 |   16.65        |
|  4.625-h6   |  6.7992     |     2.0499      |   18.58        |
|  5.0-h8     |  6.7785     |     2.0448      |   20.09        |
|  5.0-h8-ev  |  6.9376     |     2.0430      |   20.09        |