README.md

metadata

pipeline_tag: text-generation
inference:
  parameters:
    temperature: 0.2
    top_p: 0.95
widget:
  - text: 'def print_hello_world():'
    example_title: Hello world
    group: Python
datasets:
  - bigcode/the-stack-v2-train
license: bigcode-openrail-m
library_name: transformers
tags:
  - code
  - mlx
base_model: bigcode/starcoder2-15b
model-index:
  - name: starcoder2-15b
    results:
      - task:
          type: text-generation
        dataset:
          name: CruxEval-I
          type: cruxeval-i
        metrics:
          - type: pass@1
            value: 48.1
      - task:
          type: text-generation
        dataset:
          name: DS-1000
          type: ds-1000
        metrics:
          - type: pass@1
            value: 33.8
      - task:
          type: text-generation
        dataset:
          name: GSM8K (PAL)
          type: gsm8k-pal
        metrics:
          - type: accuracy
            value: 65.1
      - task:
          type: text-generation
        dataset:
          name: HumanEval+
          type: humanevalplus
        metrics:
          - type: pass@1
            value: 37.8
      - task:
          type: text-generation
        dataset:
          name: HumanEval
          type: humaneval
        metrics:
          - type: pass@1
            value: 46.3
      - task:
          type: text-generation
        dataset:
          name: RepoBench-v1.1
          type: repobench-v1.1
        metrics:
          - type: edit-smiliarity
            value: 74.08

mlx-community/bigcode-starcoder2-15b-8bit

The Model mlx-community/bigcode-starcoder2-15b-8bit was converted to MLX format from bigcode/starcoder2-15b using mlx-lm version 0.21.1 by Focused.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("mlx-community/bigcode-starcoder2-15b-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)

---

Focused is a technology company at the forefront of AI-driven development, empowering organizations to unlock the full potential of artificial intelligence. From integrating innovative models into existing systems to building scalable, modern AI infrastructures, we specialize in delivering tailored, incremental solutions that meet you where you are. Curious how we can help with your AI next project? Get in Touch