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oobabooga_-_CodeBooga-34B-v0.1-gguf
RichardErkhov/oobabooga_-_CodeBooga-34B-v0.1-gguf
oobabooga_-_CodeBooga-34B-v0.1-gguf is a machine learning model from RichardErkhov. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
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.gguf442 GB · 100%
At a glance
- Access
- Public
- Created
- Sep 13, 2024
- Updated
- Sep 14, 2024
- SHA
- fb4cb5d2
Model card
From the Hugging Face model README
Quantization made by Richard Erkhov.
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 | Q2_K | 11.65GB |
| CodeBooga-34B-v0.1.IQ3_XS.gguf | IQ3_XS | 12.93GB |
| CodeBooga-34B-v0.1.IQ3_S.gguf | IQ3_S | 13.65GB |
| CodeBooga-34B-v0.1.Q3_K_S.gguf | Q3_K_S | 13.6GB |
| CodeBooga-34B-v0.1.IQ3_M.gguf | IQ3_M | 14.18GB |
| CodeBooga-34B-v0.1.Q3_K.gguf | Q3_K | 15.19GB |
| CodeBooga-34B-v0.1.Q3_K_M.gguf | Q3_K_M | 15.19GB |
| CodeBooga-34B-v0.1.Q3_K_L.gguf | Q3_K_L | 16.55GB |
| CodeBooga-34B-v0.1.IQ4_XS.gguf | IQ4_XS | 16.99GB |
| CodeBooga-34B-v0.1.Q4_0.gguf | Q4_0 | 17.74GB |
| CodeBooga-34B-v0.1.IQ4_NL.gguf | IQ4_NL | 17.92GB |
| CodeBooga-34B-v0.1.Q4_K_S.gguf | Q4_K_S | 17.87GB |
| CodeBooga-34B-v0.1.Q4_K.gguf | Q4_K | 18.83GB |
| CodeBooga-34B-v0.1.Q4_K_M.gguf | Q4_K_M | 18.83GB |
| CodeBooga-34B-v0.1.Q4_1.gguf | Q4_1 | 19.69GB |
| CodeBooga-34B-v0.1.Q5_0.gguf | Q5_0 | 21.64GB |
| CodeBooga-34B-v0.1.Q5_K_S.gguf | Q5_K_S | 21.64GB |
| CodeBooga-34B-v0.1.Q5_K.gguf | Q5_K | 22.2GB |
| CodeBooga-34B-v0.1.Q5_K_M.gguf | Q5_K_M | 22.2GB |
| CodeBooga-34B-v0.1.Q5_1.gguf | Q5_1 | 23.59GB |
| CodeBooga-34B-v0.1.Q6_K.gguf | Q6_K | 25.78GB |
| 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:
It was created with the BlockMerge Gradient script, the same one that was used to create MythoMax-L2-13b, and with the same settings. The following YAML was used:
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:
- This one
- A second variant generated with
model_path1andmodel_path2swapped in the YAML above, which I called CodeBooga-Reversed-34B-v0.1 - WizardCoder-Python-34B-V1.0
- 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>
- Created
- Sep 13, 2024
- Updated
- Sep 14, 2024