Text Generation
Transformers
Safetensors
llama
trl
dpo
Generated from Trainer
text-generation-inference
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("stojchet/jd2")
model = AutoModelForCausalLM.from_pretrained("stojchet/jd2")Quick Links
jd2
This model is a fine-tuned version of deepseek-ai/deepseek-coder-1.3b-base on the generator dataset.
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 64
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
Framework versions
- Transformers 4.43.0.dev0
- Pytorch 2.2.2+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
- Downloads last month
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="stojchet/jd2")