metadata
license: apache-2.0
datasets:
- bigcode/the-stack
- bigcode/the-stack-v2
- bigcode/starcoderdata
- bigcode/commitpack
library_name: mlx
tags:
- code
- mlx
base_model: JetBrains/Mellum-4b-sft-python
pipeline_tag: text-generation
model-index:
- name: Mellum-4b-sft-python
results:
- task:
type: text-generation
dataset:
name: RepoBench 1.1 (Python)
type: tianyang/repobench_python_v1.1
metrics:
- type: exact_match
value: 0.2837
name: EM
verified: false
- type: exact_match
value: 0.2987
name: EM ≤ 8k
verified: false
- type: exact_match
value: 0.2924
name: EM
verified: false
- type: exact_match
value: 0.306
name: EM
verified: false
- type: exact_match
value: 0.2977
name: EM
verified: false
- type: exact_match
value: 0.268
name: EM
verified: false
- type: exact_match
value: 0.2543
name: EM
verified: false
- task:
type: text-generation
dataset:
name: SAFIM
type: gonglinyuan/safim
metrics:
- type: pass@1
value: 0.4212
name: pass@1
verified: false
- type: pass@1
value: 0.3316
name: pass@1
verified: false
- type: pass@1
value: 0.3611
name: pass@1
verified: false
- type: pass@1
value: 0.571
name: pass@1
verified: false
- task:
type: text-generation
dataset:
name: HumanEval Infilling (Single-Line)
type: loubnabnl/humaneval_infilling
metrics:
- type: pass@1
value: 0.8045
name: pass@1
verified: false
- type: pass@1
value: 0.4819
name: pass@1
verified: false
- type: pass@1
value: 0.3768
name: pass@1
verified: false
mlx-community/Mellum-4b-sft-python-8bit
This model mlx-community/Mellum-4b-sft-python-8bit was converted to MLX format from JetBrains/Mellum-4b-sft-python using mlx-lm version 0.25.2.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/Mellum-4b-sft-python-8bit")
prompt = "hello"
if tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, add_generation_prompt=True
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)