Converted version of CodeLlama-34b-Instruct-hf to 4-bit using bitsandbytes. For more information
about the model, refer to the model's page.
Impact on performance
We evaluated the models using a panel of giga-models (GPT-4o, Gemini Pro 1.5, and Claude-Sonnet 3.5). The scoring ranged from 0, indicating a model unsuitable
for the task, to 5, representing a model that fully met expectations. The evaluation was based on 67 instructions across four programming languages: Python,
Java, JavaScript, and Pseudo-code. All tests were conducted in a French-language context, and models were heavily penalized if they responded in another language,
even if the response was technically correct.
model |
score |
# params (Billion) |
size (GB) |
gemini-1.5-pro |
4.51 |
NA |
NA |
gpt-4o |
4.51 |
NA |
NA |
claude3.5-sonnet |
4.49 |
NA |
NA |
Qwen/Qwen2.5-Coder-32B-Instruct |
4.41 |
32.8 |
65.6 |
Qwen/Qwen2.5-32B-Instruct |
4.40 |
32.8 |
65.6 |
cmarkea/Qwen2.5-32B-Instruct-4bit |
4.36 |
32.8 |
16.4 |
deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct |
4.24 |
15.7 |
31.4 |
meta-llama/Meta-Llama-3.1-70B-Instruct |
4.23 |
70.06 |
140.12 |
cmarkea/Meta-Llama-3.1-70B-Instruct-4bit |
4.14 |
70.06 |
35.3 |
cmarkea/Mixtral-8x7B-Instruct-v0.1-4bit |
3.8 |
46.7 |
23.35 |
meta-llama/Meta-Llama-3.1-8B-Instruct |
3.73 |
8.03 |
16.06 |
mistralai/Mixtral-8x7B-Instruct-v0.1 |
3.33 |
46.7 |
93.4 |
codellama/CodeLlama-13b-Instruct-hf |
3.33 |
13 |
26 |
codellama/CodeLlama-34b-Instruct-hf |
3.27 |
33.7 |
67.4 |
codellama/CodeLlama-7b-Instruct-hf |
3.19 |
6.74 |
13.48 |
cmarkea/CodeLlama-34b-Instruct-hf-4bit |
3.12 |
33.7 |
16.85 |
codellama/CodeLlama-70b-Instruct-hf |
1.82 |
69 |
138 |
cmarkea/CodeLlama-70b-Instruct-hf-4bit |
1.64 |
69 |
34.5 |