Instructions to use CausalNLP/gpt2-multilingual-20-zh-repair_3epochs_lr1e-4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CausalNLP/gpt2-multilingual-20-zh-repair_3epochs_lr1e-4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="CausalNLP/gpt2-multilingual-20-zh-repair_3epochs_lr1e-4")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("CausalNLP/gpt2-multilingual-20-zh-repair_3epochs_lr1e-4") model = AutoModelForMultimodalLM.from_pretrained("CausalNLP/gpt2-multilingual-20-zh-repair_3epochs_lr1e-4") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use CausalNLP/gpt2-multilingual-20-zh-repair_3epochs_lr1e-4 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "CausalNLP/gpt2-multilingual-20-zh-repair_3epochs_lr1e-4" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "CausalNLP/gpt2-multilingual-20-zh-repair_3epochs_lr1e-4", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/CausalNLP/gpt2-multilingual-20-zh-repair_3epochs_lr1e-4
- SGLang
How to use CausalNLP/gpt2-multilingual-20-zh-repair_3epochs_lr1e-4 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 "CausalNLP/gpt2-multilingual-20-zh-repair_3epochs_lr1e-4" \ --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": "CausalNLP/gpt2-multilingual-20-zh-repair_3epochs_lr1e-4", "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 "CausalNLP/gpt2-multilingual-20-zh-repair_3epochs_lr1e-4" \ --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": "CausalNLP/gpt2-multilingual-20-zh-repair_3epochs_lr1e-4", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use CausalNLP/gpt2-multilingual-20-zh-repair_3epochs_lr1e-4 with Docker Model Runner:
docker model run hf.co/CausalNLP/gpt2-multilingual-20-zh-repair_3epochs_lr1e-4
File size: 779 Bytes
2e4ec38 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | {
"activation_function": "gelu_new",
"architectures": [
"GPT2LMHeadModel"
],
"attn_pdrop": 0.0,
"block_size": 1024,
"bos_token_id": 3,
"dropout": 0.0,
"dtype": "bfloat16",
"embd_pdrop": 0.0,
"eos_token_id": 4,
"initializer_range": 0.02,
"layer_norm_epsilon": 1e-05,
"model_type": "gpt2",
"n_embd": 768,
"n_head": 12,
"n_inner": null,
"n_layer": 12,
"n_positions": 1024,
"reorder_and_upcast_attn": false,
"resid_pdrop": 0.0,
"scale_attn_by_inverse_layer_idx": false,
"scale_attn_weights": true,
"summary_activation": null,
"summary_first_dropout": 0.0,
"summary_proj_to_labels": true,
"summary_type": "cls_index",
"summary_use_proj": true,
"transformers_version": "4.57.3",
"use_cache": true,
"vocab_size": 119547
}
|