README.md

metadata

base_model: Locutusque/TinyMistral-248M
datasets:
  - Skylion007/openwebtext
inference: false
language:
  - en
license: apache-2.0
model_creator: Locutusque
model_name: TinyMistral-248M
pipeline_tag: text-generation
quantized_by: afrideva
tags:
  - gguf
  - ggml
  - quantized
  - q2_k
  - q3_k_m
  - q4_k_m
  - q5_k_m
  - q6_k
  - q8_0

Locutusque/TinyMistral-248M-GGUF

Quantized GGUF model files for TinyMistral-248M from Locutusque

Name	Quant method	Size
tinymistral-248m.q2_k.gguf	q2_k	116.20 MB
tinymistral-248m.q3_k_m.gguf	q3_k_m	131.01 MB
tinymistral-248m.q4_k_m.gguf	q4_k_m	156.60 MB
tinymistral-248m.q5_k_m.gguf	q5_k_m	180.16 MB
tinymistral-248m.q6_k.gguf	q6_k	205.20 MB
tinymistral-248m.q8_0.gguf	q8_0	265.26 MB

Original Model Card:

A pre-trained language model, based on the Mistral 7B model, has been scaled down to approximately 248 million parameters. This model has been trained on 7,320,000 examples. This model isn't intended for direct use but for fine-tuning on a downstream task. This model should have a context length of around 32,768 tokens.

During evaluation on InstructMix, this model achieved an average perplexity score of 6.3. This is the final epoch planned for this model.

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	24.18
ARC (25-shot)	20.82
HellaSwag (10-shot)	26.98
MMLU (5-shot)	23.11
TruthfulQA (0-shot)	46.89
Winogrande (5-shot)	50.75
GSM8K (5-shot)	0.0
DROP (3-shot)	0.74