Text Generation
Transformers
PyTorch
TensorBoard
gpt2
Generated from Trainer
text-generation-inference
Instructions to use psxjp5/mlm_old with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use psxjp5/mlm_old with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="psxjp5/mlm_old")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("psxjp5/mlm_old") model = AutoModelForCausalLM.from_pretrained("psxjp5/mlm_old") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use psxjp5/mlm_old with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "psxjp5/mlm_old" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "psxjp5/mlm_old", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/psxjp5/mlm_old
- SGLang
How to use psxjp5/mlm_old with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "psxjp5/mlm_old" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "psxjp5/mlm_old", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "psxjp5/mlm_old" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "psxjp5/mlm_old", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use psxjp5/mlm_old with Docker Model Runner:
docker model run hf.co/psxjp5/mlm_old
mlm_new
This model is a fine-tuned version of gpt2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 4.0711
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: 3e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Perplexity |
|---|---|---|---|---|
| 12.948 | 0.99 | 22 | 5.1466 | 171.85 |
| 4.061 | 1.98 | 44 | 4.3114 | 74.54 |
| 3.7125 | 2.97 | 66 | 4.0807 | 59.19 |
| 3.6033 | 3.96 | 88 | 4.0553 | 57.70 |
| 3.5032 | 4.94 | 110 | 4.0514 | 57.48 |
| 3.4427 | 5.93 | 132 | 4.0879 | 59.61 |
| 3.3968 | 6.92 | 154 | 4.0711 | 58.62 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.2
- Tokenizers 0.13.3
- Downloads last month
- 4
Model tree for psxjp5/mlm_old
Base model
openai-community/gpt2