Text Generation
Transformers
Safetensors
PyTorch
English
pldrllm
large-language-model
power-law-decoder-representations
power-law-graph-attention
pldr-llm
kv-cache
g-cache
kvg-cache
custom_code
Instructions to use fromthesky/PLDR-LLM-v51-110M-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fromthesky/PLDR-LLM-v51-110M-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="fromthesky/PLDR-LLM-v51-110M-2", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("fromthesky/PLDR-LLM-v51-110M-2", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use fromthesky/PLDR-LLM-v51-110M-2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "fromthesky/PLDR-LLM-v51-110M-2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "fromthesky/PLDR-LLM-v51-110M-2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/fromthesky/PLDR-LLM-v51-110M-2
- SGLang
How to use fromthesky/PLDR-LLM-v51-110M-2 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 "fromthesky/PLDR-LLM-v51-110M-2" \ --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": "fromthesky/PLDR-LLM-v51-110M-2", "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 "fromthesky/PLDR-LLM-v51-110M-2" \ --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": "fromthesky/PLDR-LLM-v51-110M-2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use fromthesky/PLDR-LLM-v51-110M-2 with Docker Model Runner:
docker model run hf.co/fromthesky/PLDR-LLM-v51-110M-2
| { | |
| "A_dff": 170, | |
| "architectures": [ | |
| "PldrllmForCausalLM" | |
| ], | |
| "attention_bias": true, | |
| "attention_dropout": 0.0, | |
| "auto_map": { | |
| "AutoConfig": "configuration_pldrllm.PldrllmConfig", | |
| "AutoModelForCausalLM": "modeling_pldrllm.PldrllmForCausalLM" | |
| }, | |
| "bos_token_id": 2, | |
| "cache_first_G": false, | |
| "custom_G_type": null, | |
| "eos_token_id": 3, | |
| "final_bias": true, | |
| "glu_bias": true, | |
| "head_dim": 64, | |
| "hidden_act": "silu", | |
| "hidden_size": 896, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 2389, | |
| "layer_norm_eps": 1e-06, | |
| "max_position_embeddings": 1024, | |
| "model_type": "pldrllm", | |
| "num_attention_heads": 14, | |
| "num_denseA": 2, | |
| "num_hidden_layers": 5, | |
| "num_reslayerA": 8, | |
| "output_pldr_attentions": false, | |
| "pad_token_id": 0, | |
| "reference_rope": true, | |
| "rope_scaling": null, | |
| "rope_theta": 10000.0, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.56.1", | |
| "use_cache": true, | |
| "vocab_size": 32000 | |
| } | |