metadata

license: apache-2.0
language:
  - en
  - code
datasets:
  - open-phi/programming_books_llama
  - open-phi/textbooks
tags:
  - merge
  - computer science
inference:
  parameters:
    do_sample: true
    temperature: 0.7
    top_p: 0.2
    top_k: 14
    max_new_tokens: 250
    repetition_penalty: 1.16

TinyMistral-248M-v2.5

This model was created by merging TinyMistral-248M-v1 and v2, then further pretraining on synthetic textbooks. The resulting model's performance is superior to both, after personal evaluation.

During training, this model reached an average perplexity score of 4, outperforming V1 by nearly 7x, and V2 by almost 4x.

You can use the following config to reproduce the merged model:

base_model: Locutusque/TinyMistral-248M-v2
dtype: float16
merge_method: ties
parameters:
  int8_mask: 1.0
  normalize: 1.0
slices:
- sources:
  - layer_range: [0, 12]
    model: Locutusque/TinyMistral-248M
    parameters:
      density: [1.0, 0.7, 0.1]
      weight: 1.0
  - layer_range: [0, 12]
    model: Locutusque/TinyMistral-248M-v2
    parameters:
      density: 0.5
      weight: [0.0, 0.3, 0.7, 1.0]

This model can also answer basic questions, without needing to do any fine-tuning. Go ahead and try in the inference API.