Text Generation
Transformers
PyTorch
Persian
English
ysnrfd
From_Scratch
Custom
YSNRFD
LLM
Persian_LLM
Instructions to use ysn-rfd/ysnrfd-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ysn-rfd/ysnrfd-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ysn-rfd/ysnrfd-base")# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("ysn-rfd/ysnrfd-base", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use ysn-rfd/ysnrfd-base with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ysn-rfd/ysnrfd-base" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ysn-rfd/ysnrfd-base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/ysn-rfd/ysnrfd-base
- SGLang
How to use ysn-rfd/ysnrfd-base 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 "ysn-rfd/ysnrfd-base" \ --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": "ysn-rfd/ysnrfd-base", "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 "ysn-rfd/ysnrfd-base" \ --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": "ysn-rfd/ysnrfd-base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use ysn-rfd/ysnrfd-base with Docker Model Runner:
docker model run hf.co/ysn-rfd/ysnrfd-base
REPORT ANY PROBLEMS IN MODEL LOADING AND INFERENCE
Model Details
WARNINNGS: This Model IS Pre-Trained, in the future will be finetuned.
Model Description
The First Persian LLM By YSNRFD, This Model support Only English text Inputs, In The Future I Want Add Persian Language Support.
- Developed by: ysnrfd
- Funded by: ysnrfd
- Shared by: ysnrfd
- Model type: LLM
- Language(s) (NLP): English
- License: ysnrfd LICENSE
Training Data
wikitext2
Training Hyperparameters
- Training regime: fp32 mixed precision
Evaluation
Not Yet
Testing Data, Factors & Metrics
ysnrfd en testing data
Testing Data
Not Yet
Summary
The Fisrt Persian LLM Trained From Scratch (Size Like SLM)
- Hardware Type: Nvidia Tesla T4
- Hours used: 11H
- Cloud Provider: Google Colab
Model Architecture and Objective
YSNRFD Architecture
Hardware
Nvidia Tesla T4
Software
Python Code, From Scratch, Pytorch
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