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

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

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

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


CodeBooga-34B-v0.1 - GGUF
- Model creator: https://huggingface.co/oobabooga/
- Original model: https://huggingface.co/oobabooga/CodeBooga-34B-v0.1/


| Name | Quant method | Size |
| ---- | ---- | ---- |
| [CodeBooga-34B-v0.1.Q2_K.gguf](https://huggingface.co/RichardErkhov/oobabooga_-_CodeBooga-34B-v0.1-gguf/blob/main/CodeBooga-34B-v0.1.Q2_K.gguf) | Q2_K | 11.65GB |
| [CodeBooga-34B-v0.1.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/oobabooga_-_CodeBooga-34B-v0.1-gguf/blob/main/CodeBooga-34B-v0.1.IQ3_XS.gguf) | IQ3_XS | 12.93GB |
| [CodeBooga-34B-v0.1.IQ3_S.gguf](https://huggingface.co/RichardErkhov/oobabooga_-_CodeBooga-34B-v0.1-gguf/blob/main/CodeBooga-34B-v0.1.IQ3_S.gguf) | IQ3_S | 13.65GB |
| [CodeBooga-34B-v0.1.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/oobabooga_-_CodeBooga-34B-v0.1-gguf/blob/main/CodeBooga-34B-v0.1.Q3_K_S.gguf) | Q3_K_S | 13.6GB |
| [CodeBooga-34B-v0.1.IQ3_M.gguf](https://huggingface.co/RichardErkhov/oobabooga_-_CodeBooga-34B-v0.1-gguf/blob/main/CodeBooga-34B-v0.1.IQ3_M.gguf) | IQ3_M | 14.18GB |
| [CodeBooga-34B-v0.1.Q3_K.gguf](https://huggingface.co/RichardErkhov/oobabooga_-_CodeBooga-34B-v0.1-gguf/blob/main/CodeBooga-34B-v0.1.Q3_K.gguf) | Q3_K | 15.19GB |
| [CodeBooga-34B-v0.1.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/oobabooga_-_CodeBooga-34B-v0.1-gguf/blob/main/CodeBooga-34B-v0.1.Q3_K_M.gguf) | Q3_K_M | 15.19GB |
| [CodeBooga-34B-v0.1.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/oobabooga_-_CodeBooga-34B-v0.1-gguf/blob/main/CodeBooga-34B-v0.1.Q3_K_L.gguf) | Q3_K_L | 16.55GB |
| [CodeBooga-34B-v0.1.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/oobabooga_-_CodeBooga-34B-v0.1-gguf/blob/main/CodeBooga-34B-v0.1.IQ4_XS.gguf) | IQ4_XS | 16.99GB |
| [CodeBooga-34B-v0.1.Q4_0.gguf](https://huggingface.co/RichardErkhov/oobabooga_-_CodeBooga-34B-v0.1-gguf/blob/main/CodeBooga-34B-v0.1.Q4_0.gguf) | Q4_0 | 17.74GB |
| [CodeBooga-34B-v0.1.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/oobabooga_-_CodeBooga-34B-v0.1-gguf/blob/main/CodeBooga-34B-v0.1.IQ4_NL.gguf) | IQ4_NL | 17.92GB |
| [CodeBooga-34B-v0.1.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/oobabooga_-_CodeBooga-34B-v0.1-gguf/blob/main/CodeBooga-34B-v0.1.Q4_K_S.gguf) | Q4_K_S | 17.87GB |
| [CodeBooga-34B-v0.1.Q4_K.gguf](https://huggingface.co/RichardErkhov/oobabooga_-_CodeBooga-34B-v0.1-gguf/blob/main/CodeBooga-34B-v0.1.Q4_K.gguf) | Q4_K | 18.83GB |
| [CodeBooga-34B-v0.1.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/oobabooga_-_CodeBooga-34B-v0.1-gguf/blob/main/CodeBooga-34B-v0.1.Q4_K_M.gguf) | Q4_K_M | 18.83GB |
| [CodeBooga-34B-v0.1.Q4_1.gguf](https://huggingface.co/RichardErkhov/oobabooga_-_CodeBooga-34B-v0.1-gguf/blob/main/CodeBooga-34B-v0.1.Q4_1.gguf) | Q4_1 | 19.69GB |
| [CodeBooga-34B-v0.1.Q5_0.gguf](https://huggingface.co/RichardErkhov/oobabooga_-_CodeBooga-34B-v0.1-gguf/blob/main/CodeBooga-34B-v0.1.Q5_0.gguf) | Q5_0 | 21.64GB |
| [CodeBooga-34B-v0.1.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/oobabooga_-_CodeBooga-34B-v0.1-gguf/blob/main/CodeBooga-34B-v0.1.Q5_K_S.gguf) | Q5_K_S | 21.64GB |
| [CodeBooga-34B-v0.1.Q5_K.gguf](https://huggingface.co/RichardErkhov/oobabooga_-_CodeBooga-34B-v0.1-gguf/blob/main/CodeBooga-34B-v0.1.Q5_K.gguf) | Q5_K | 22.2GB |
| [CodeBooga-34B-v0.1.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/oobabooga_-_CodeBooga-34B-v0.1-gguf/blob/main/CodeBooga-34B-v0.1.Q5_K_M.gguf) | Q5_K_M | 22.2GB |
| [CodeBooga-34B-v0.1.Q5_1.gguf](https://huggingface.co/RichardErkhov/oobabooga_-_CodeBooga-34B-v0.1-gguf/blob/main/CodeBooga-34B-v0.1.Q5_1.gguf) | Q5_1 | 23.59GB |
| [CodeBooga-34B-v0.1.Q6_K.gguf](https://huggingface.co/RichardErkhov/oobabooga_-_CodeBooga-34B-v0.1-gguf/blob/main/CodeBooga-34B-v0.1.Q6_K.gguf) | Q6_K | 25.78GB |
| [CodeBooga-34B-v0.1.Q8_0.gguf](https://huggingface.co/RichardErkhov/oobabooga_-_CodeBooga-34B-v0.1-gguf/blob/main/CodeBooga-34B-v0.1.Q8_0.gguf) | Q8_0 | 33.39GB |




Original model description:
---
license: llama2
---

# CodeBooga-34B-v0.1

This is a merge between the following two models:

1) [Phind-CodeLlama-34B-v2](https://huggingface.co/Phind/Phind-CodeLlama-34B-v2)
2) [WizardCoder-Python-34B-V1.0](https://huggingface.co/WizardLM/WizardCoder-Python-34B-V1.0)

It was created with the [BlockMerge Gradient script](https://github.com/Gryphe/BlockMerge_Gradient), the same one that was used to create [MythoMax-L2-13b](https://huggingface.co/Gryphe/MythoMax-L2-13b), and with the same settings. The following YAML was used:

```yaml
model_path1: "Phind_Phind-CodeLlama-34B-v2_safetensors"
model_path2: "WizardLM_WizardCoder-Python-34B-V1.0_safetensors"
output_model_path: "CodeBooga-34B-v0.1"
operations:
  - operation: lm_head # Single tensor
    filter: "lm_head"
    gradient_values: [0.75]
  - operation: embed_tokens # Single tensor
    filter: "embed_tokens"
    gradient_values: [0.75]
  - operation: self_attn
    filter: "self_attn"
    gradient_values: [0.75, 0.25]
  - operation: mlp
    filter: "mlp"
    gradient_values: [0.25, 0.75]
  - operation: layernorm
    filter: "layernorm"
    gradient_values: [0.5, 0.5]
  - operation: modelnorm # Single tensor
    filter: "model.norm"
    gradient_values: [0.75]
```

## Prompt format

Both base models use the Alpaca format, so it should be used for this one as well.

```
Below is an instruction that describes a task. Write a response that appropriately completes the request.

### Instruction:
Your instruction

### Response:
Bot reply

### Instruction:
Another instruction

### Response:
Bot reply
```

## Evaluation

(This is not very scientific, so bear with me.)

I made a quick experiment where I asked a set of 3 Python and 3 Javascript questions (real world, difficult questions with nuance) to the following models:

1) This one
2) A second variant generated with `model_path1` and `model_path2` swapped in the YAML above, which I called CodeBooga-Reversed-34B-v0.1
3) WizardCoder-Python-34B-V1.0
4) Phind-CodeLlama-34B-v2

Specifically, I used 4.250b EXL2 quantizations of each. I then sorted the responses for each question by quality, and attributed the following scores:

* 4th place: 0
* 3rd place: 1
* 2nd place: 2
* 1st place: 4

The resulting cumulative scores were:

* CodeBooga-34B-v0.1: 22
* WizardCoder-Python-34B-V1.0: 12
* Phind-CodeLlama-34B-v2: 7
* CodeBooga-Reversed-34B-v0.1: 1

CodeBooga-34B-v0.1 performed very well, while its variant performed poorly, so I uploaded the former but not the latter.

## Quantized versions

### GGUF

TheBloke has kindly provided GGUF quantizations for llama.cpp:

https://huggingface.co/TheBloke/CodeBooga-34B-v0.1-GGUF

<a href="https://ko-fi.com/oobabooga"><img src="https://i.imgur.com/UJlEAYw.png"></a>

