Instructions to use Serdar404/RecGPT-10M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Serdar404/RecGPT-10M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Serdar404/RecGPT-10M", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("Serdar404/RecGPT-10M", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Serdar404/RecGPT-10M with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Serdar404/RecGPT-10M" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Serdar404/RecGPT-10M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Serdar404/RecGPT-10M
- SGLang
How to use Serdar404/RecGPT-10M 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 "Serdar404/RecGPT-10M" \ --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": "Serdar404/RecGPT-10M", "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 "Serdar404/RecGPT-10M" \ --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": "Serdar404/RecGPT-10M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Serdar404/RecGPT-10M with Docker Model Runner:
docker model run hf.co/Serdar404/RecGPT-10M
| { | |
| "dataset": "s33c67-10m.parquet", | |
| "tokenizer": "s33c67-10m-bpe", | |
| "run_name": "recgpt-10m-submission", | |
| "seed": 0, | |
| "data_seed": 0, | |
| "microbatch_tok": 32768, | |
| "total_batch_tok": 32768, | |
| "sequence_len": 256, | |
| "epochs": 10, | |
| "checkpoint_track": "strict-small", | |
| "max_tokens": -1, | |
| "lr_embed": 0.005, | |
| "lr_block": 0.02, | |
| "min_lr": 0.0, | |
| "wd_adam": 0.005, | |
| "wd_muon": 0.1, | |
| "adam_beta1": 0.9, | |
| "adam_beta2": 0.997, | |
| "muon_momentum": 0.95, | |
| "warmup_ratio": 0.0, | |
| "cooldown_ratio": 0.2, | |
| "max_grad_norm": 2.0, | |
| "nl_mult": 0.01, | |
| "nl_depth": 2, | |
| "nl_hidden": -1, | |
| "nl_intermediate": 5120, | |
| "nl_lr": 0.004, | |
| "nl_wd": 0.01, | |
| "nl_momentum": 0.95, | |
| "torch_compile": true, | |
| "use_wandb": true, | |
| "wandb_project": "bblm26-recgpt", | |
| "log_every": 10, | |
| "model_config": { | |
| "transformers_version": "5.9.0", | |
| "architectures": [ | |
| "RecGPTForCausalLM" | |
| ], | |
| "output_hidden_states": false, | |
| "return_dict": true, | |
| "dtype": "float32", | |
| "chunk_size_feed_forward": 0, | |
| "is_encoder_decoder": false, | |
| "id2label": { | |
| "0": "LABEL_0", | |
| "1": "LABEL_1" | |
| }, | |
| "label2id": { | |
| "LABEL_0": 0, | |
| "LABEL_1": 1 | |
| }, | |
| "problem_type": null, | |
| "_name_or_path": "", | |
| "pad_token_id": 0, | |
| "tie_word_embeddings": false, | |
| "vocab_size": 32768, | |
| "hidden_size": 768, | |
| "embedding_size": 192, | |
| "head_dim": 64, | |
| "num_heads": 12, | |
| "intermediate_size": 12288, | |
| "recursive_depth": 16, | |
| "max_position_embeddings": 1024, | |
| "is_decoder": true, | |
| "use_cache": false, | |
| "auto_map": { | |
| "AutoConfig": "modeling_recgpt.RecGPTConfig", | |
| "AutoModelForCausalLM": "modeling_recgpt.RecGPTForCausalLM" | |
| }, | |
| "model_type": "recgpt", | |
| "output_attentions": false | |
| } | |
| } |