Text Generation
Transformers
PyTorch
TensorBoard
Safetensors
English
gpt2
Text-Generation
text-generation-inference
Instructions to use SRDdev/ScriptForge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SRDdev/ScriptForge with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="SRDdev/ScriptForge")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("SRDdev/ScriptForge") model = AutoModelForCausalLM.from_pretrained("SRDdev/ScriptForge") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use SRDdev/ScriptForge with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "SRDdev/ScriptForge" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "SRDdev/ScriptForge", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/SRDdev/ScriptForge
- SGLang
How to use SRDdev/ScriptForge 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 "SRDdev/ScriptForge" \ --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": "SRDdev/ScriptForge", "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 "SRDdev/ScriptForge" \ --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": "SRDdev/ScriptForge", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use SRDdev/ScriptForge with Docker Model Runner:
docker model run hf.co/SRDdev/ScriptForge
Training in progress, step 2500
Browse files- config.json +1 -1
- pytorch_model.bin +2 -2
- runs/Feb26_12-40-03_6c7e37021706/1677415333.9679577/events.out.tfevents.1677415333.6c7e37021706.2142.1 +3 -0
- runs/Feb26_12-40-03_6c7e37021706/events.out.tfevents.1677415333.6c7e37021706.2142.0 +3 -0
- runs/Feb26_12-45-16_6c7e37021706/1677415527.0114596/events.out.tfevents.1677415527.6c7e37021706.2142.3 +3 -0
- runs/Feb26_12-45-16_6c7e37021706/events.out.tfevents.1677415527.6c7e37021706.2142.2 +3 -0
- training_args.bin +2 -2
config.json
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"use_cache": true,
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