Instructions to use Kalslice/Wikitext90 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kalslice/Wikitext90 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Kalslice/Wikitext90")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Kalslice/Wikitext90") model = AutoModelForCausalLM.from_pretrained("Kalslice/Wikitext90", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Kalslice/Wikitext90 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Kalslice/Wikitext90" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Kalslice/Wikitext90", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Kalslice/Wikitext90
- SGLang
How to use Kalslice/Wikitext90 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 "Kalslice/Wikitext90" \ --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": "Kalslice/Wikitext90", "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 "Kalslice/Wikitext90" \ --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": "Kalslice/Wikitext90", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Kalslice/Wikitext90 with Docker Model Runner:
docker model run hf.co/Kalslice/Wikitext90
| { | |
| "_name_or_path": "gpt2", | |
| "activation_function": "gelu_new", | |
| "architectures": [ | |
| "GPT2LMHeadModel" | |
| ], | |
| "attn_pdrop": 0.1, | |
| "bos_token_id": 50256, | |
| "embd_pdrop": 0.1, | |
| "eos_token_id": 50256, | |
| "initializer_range": 0.02, | |
| "layer_norm_epsilon": 1e-05, | |
| "model_type": "gpt2", | |
| "n_ctx": 1024, | |
| "n_embd": 768, | |
| "n_head": 12, | |
| "n_inner": null, | |
| "n_layer": 12, | |
| "n_positions": 1024, | |
| "output_attentions": true, | |
| "pruned_heads": { | |
| "3": [ | |
| 0, | |
| 4 | |
| ], | |
| "4": [ | |
| 10 | |
| ], | |
| "5": [ | |
| 0, | |
| 1, | |
| 5, | |
| 9 | |
| ], | |
| "6": [ | |
| 9, | |
| 10 | |
| ], | |
| "7": [ | |
| 1, | |
| 2, | |
| 7, | |
| 10, | |
| 11 | |
| ], | |
| "8": [ | |
| 1 | |
| ], | |
| "9": [ | |
| 0, | |
| 1, | |
| 4, | |
| 6, | |
| 9, | |
| 11 | |
| ], | |
| "10": [ | |
| 0, | |
| 1, | |
| 2, | |
| 6, | |
| 8, | |
| 10 | |
| ], | |
| "11": [ | |
| 9, | |
| 2, | |
| 5, | |
| 6 | |
| ] | |
| }, | |
| "reorder_and_upcast_attn": false, | |
| "resid_pdrop": 0.1, | |
| "scale_attn_by_inverse_layer_idx": false, | |
| "scale_attn_weights": true, | |
| "summary_activation": null, | |
| "summary_first_dropout": 0.1, | |
| "summary_proj_to_labels": true, | |
| "summary_type": "cls_index", | |
| "summary_use_proj": true, | |
| "task_specific_params": { | |
| "text-generation": { | |
| "do_sample": true, | |
| "max_length": 50 | |
| } | |
| }, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.36.2", | |
| "use_cache": true, | |
| "vocab_size": 50257 | |
| } | |