metadata
license: apache-2.0
datasets:
- bigcode/the-stack
- bigcode/the-stack-v2
- bigcode/starcoderdata
- bigcode/commitpack
library_name: transformers
tags:
- code
- mlx
- mlx-my-repo
base_model: JetBrains/Mellum-4b-sft-python
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
cnfusion/Mellum-4b-sft-python-mlx-8Bit
The Model cnfusion/Mellum-4b-sft-python-mlx-8Bit was converted to MLX format from JetBrains/Mellum-4b-sft-python using mlx-lm version 0.22.3.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("cnfusion/Mellum-4b-sft-python-mlx-8Bit")
prompt="hello"
if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, tokenize=False, add_generation_prompt=True
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)