Text Generation
Transformers
Safetensors
Vietnamese
sai
custom-code
vietnamese
causal-lm
custom_code
Instructions to use thongbuind/SAI_35M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thongbuind/SAI_35M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="thongbuind/SAI_35M", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("thongbuind/SAI_35M", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use thongbuind/SAI_35M with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "thongbuind/SAI_35M" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "thongbuind/SAI_35M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/thongbuind/SAI_35M
- SGLang
How to use thongbuind/SAI_35M 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 "thongbuind/SAI_35M" \ --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": "thongbuind/SAI_35M", "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 "thongbuind/SAI_35M" \ --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": "thongbuind/SAI_35M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use thongbuind/SAI_35M with Docker Model Runner:
docker model run hf.co/thongbuind/SAI_35M
| { | |
| "vocab_size": 10000, | |
| "max_seq_len": 2048, | |
| "dropout": 0.05, | |
| "pretrain_epochs": 1, | |
| "continued_pretrain_epochs": 5, | |
| "sft1_epochs": 5, | |
| "sft2_epochs": 1, | |
| "train_ratio": 0.95, | |
| "val_ratio": 0.04, | |
| "pretrain_learning_rate": 2e-4, | |
| "continued_pretrain_learning_rate": 1.5e-5, | |
| "sft1_learning_rate": 2e-5, | |
| "sft2_learning_rate": 1e-5, | |
| "accumulation_steps": 1, | |
| "pretrain_weight_decay": 0.2, | |
| "continued_pretrain_weight_decay": 0.1, | |
| "sft1_learning_weight_decay": 0.05, | |
| "sft2_learning_weight_decay": 0.05, | |
| "penalty_margin_weight": 0.1, | |
| "penalty_margin_detach_max": true, | |
| "penalty_entropy_weight": 0.001, | |
| "penalty_entropy_min_entropy": 0.5, | |
| "penalty_focal_weight": 0.05, | |
| "penalty_focal_gamma": 2.0 | |
| } | |