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metadata
base_model: BEE-spoke-data/smol_llama-101M-midjourney-messages
datasets:
  - pszemraj/midjourney-messages-cleaned
inference: false
license: apache-2.0
metrics:
  - accuracy
model_creator: BEE-spoke-data
model_name: smol_llama-101M-midjourney-messages
pipeline_tag: text-generation
quantized_by: afrideva
tags:
  - generated_from_trainer
  - gguf
  - ggml
  - quantized
  - q2_k
  - q3_k_m
  - q4_k_m
  - q5_k_m
  - q6_k
  - q8_0
widget:
  - example_title: avocado chair
    text: avocado chair
  - example_title: potato
    text: A mysterious potato

BEE-spoke-data/smol_llama-101M-midjourney-messages-GGUF

Quantized GGUF model files for smol_llama-101M-midjourney-messages from BEE-spoke-data

Original Model Card:

smol_llama-101M-midjourney-messages

Given a 'partial prompt' for a text2image model, this generates additional relevant text to include for a full prompt.

example

Model description

This model is a fine-tuned version of BEE-spoke-data/smol_llama-101M-GQA on the pszemraj/midjourney-messages-cleaned dataset. It achieves the following results on the evaluation set:

  • Loss: 2.8431
  • Accuracy: 0.4682

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.00025
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 17056
  • gradient_accumulation_steps: 16
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08
  • lr_scheduler_type: inverse_sqrt
  • lr_scheduler_warmup_ratio: 0.05
  • num_epochs: 1.0