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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("psxjp5/mlm_old") model = AutoModelForCausalLM.from_pretrained("psxjp5/mlm_old", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- 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
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Download README.md from psxjp5/mlm_old: direct link, hf CLI and curl.
- Browser
- Download file 1.71 kB
-
https://huggingface.co/psxjp5/mlm_old/resolve/main/README.md
- Command line
-
hf download hf://psxjp5/mlm_old/README.md
-
curl -L -o README.md https://huggingface.co/psxjp5/mlm_old/resolve/main/README.md
1.71 kB
| license: mit | |
| base_model: gpt2 | |
| tags: | |
| - generated_from_trainer | |
| model-index: | |
| - name: mlm_new | |
| results: [] | |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
| should probably proofread and complete it, then remove this comment. --> | |
| # mlm_new | |
| This model is a fine-tuned version of [gpt2](https://huggingface.co/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 | |