Text Generation
Transformers
Safetensors
English
llama
unlearn
machine-unlearning
llm-unlearning
data-privacy
large-language-models
trustworthy-ai
trustworthy-machine-learning
language-model
text-generation-inference
Instructions to use OPTML-Group/SimNPO-TOFU-forget05-Llama-2-7b-chat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OPTML-Group/SimNPO-TOFU-forget05-Llama-2-7b-chat with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="OPTML-Group/SimNPO-TOFU-forget05-Llama-2-7b-chat")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("OPTML-Group/SimNPO-TOFU-forget05-Llama-2-7b-chat") model = AutoModelForMultimodalLM.from_pretrained("OPTML-Group/SimNPO-TOFU-forget05-Llama-2-7b-chat") - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use OPTML-Group/SimNPO-TOFU-forget05-Llama-2-7b-chat with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "OPTML-Group/SimNPO-TOFU-forget05-Llama-2-7b-chat" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OPTML-Group/SimNPO-TOFU-forget05-Llama-2-7b-chat", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/OPTML-Group/SimNPO-TOFU-forget05-Llama-2-7b-chat
- SGLang
How to use OPTML-Group/SimNPO-TOFU-forget05-Llama-2-7b-chat 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 "OPTML-Group/SimNPO-TOFU-forget05-Llama-2-7b-chat" \ --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": "OPTML-Group/SimNPO-TOFU-forget05-Llama-2-7b-chat", "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 "OPTML-Group/SimNPO-TOFU-forget05-Llama-2-7b-chat" \ --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": "OPTML-Group/SimNPO-TOFU-forget05-Llama-2-7b-chat", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use OPTML-Group/SimNPO-TOFU-forget05-Llama-2-7b-chat with Docker Model Runner:
docker model run hf.co/OPTML-Group/SimNPO-TOFU-forget05-Llama-2-7b-chat
| { | |
| "_name_or_path": "/egr/research-optml/chongyu/NEW-BLUE/TOFU/paper_models/final_ft_noLORA_5_epochs_inst_lr1e-05_llama2-7b_full_seed42_1/checkpoint-625/unlearned/8GPU_simnpo_grad_diff_1e-05_forget05_epoch10_batch1_accum4_beta2.5_gamma0.0_grad_diff_coeff0.1375_reffine_tuned_evalsteps_per_epoch_seed1001_1/checkpoint-62", | |
| "architectures": [ | |
| "LlamaForCausalLM" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 1, | |
| "eos_token_id": 2, | |
| "hidden_act": "silu", | |
| "hidden_size": 4096, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 11008, | |
| "max_position_embeddings": 4096, | |
| "mlp_bias": false, | |
| "model_type": "llama", | |
| "num_attention_heads": 32, | |
| "num_hidden_layers": 32, | |
| "num_key_value_heads": 32, | |
| "pad_token_id": 0, | |
| "pretraining_tp": 1, | |
| "rms_norm_eps": 1e-05, | |
| "rope_scaling": null, | |
| "rope_theta": 10000.0, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "bfloat16", | |
| "transformers_version": "4.43.0.dev0", | |
| "use_cache": false, | |
| "vocab_size": 32000 | |
| } | |