MLX
Safetensors
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mistral
Eval Results
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metadata
language:
  - en
license: apache-2.0
tags:
  - mlx
base_model: alpindale/Mistral-7B-v0.2-hf
datasets:
  - cognitivecomputations/dolphin
  - cognitivecomputations/dolphin-coder
  - cognitivecomputations/samantha-data
  - jondurbin/airoboros-2.2.1
  - teknium/openhermes-2.5
  - m-a-p/Code-Feedback
  - m-a-p/CodeFeedback-Filtered-Instruction
model-index:
  - name: dolphin-2.8-mistral-7b-v02
    results:
      - task:
          type: text-generation
        dataset:
          name: HumanEval
          type: openai_humaneval
        metrics:
          - type: pass@1
            value: 0.469
            name: pass@1
            verified: false

mlx-community/dolphin-2.8-mistral-7b-v02-4bit

This model was converted to MLX format from cognitivecomputations/dolphin-2.8-mistral-7b-v02 using mlx-lm version 0.7.0. Refer to the original model card for more details on the model.

Use with mlx

pip install mlx-lm
from mlx_lm import load, generate

model, tokenizer = load("mlx-community/dolphin-2.8-mistral-7b-v02-4bit")
response = generate(model, tokenizer, prompt="hello", verbose=True)