Instructions to use AntonClaesson/movie-plot-generator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use AntonClaesson/movie-plot-generator with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="AntonClaesson/movie-plot-generator")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("AntonClaesson/movie-plot-generator")
model = AutoModelForCausalLM.from_pretrained("AntonClaesson/movie-plot-generator")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use AntonClaesson/movie-plot-generator with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "AntonClaesson/movie-plot-generator"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "AntonClaesson/movie-plot-generator",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/AntonClaesson/movie-plot-generator

SGLang

How to use AntonClaesson/movie-plot-generator 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 "AntonClaesson/movie-plot-generator" \
    --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": "AntonClaesson/movie-plot-generator",
		"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 "AntonClaesson/movie-plot-generator" \
        --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": "AntonClaesson/movie-plot-generator",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use AntonClaesson/movie-plot-generator with Docker Model Runner:
```
docker model run hf.co/AntonClaesson/movie-plot-generator
```

AntonClaesson commited on Oct 14, 2021

Commit

72fbc7d

1 Parent(s): a5b4dab

update model card README.md

Browse files

Files changed (1) hide show

README.md +6 -2

README.md CHANGED Viewed

@@ -31,16 +31,20 @@ More information needed
 The following hyperparameters were used during training:
 - learning_rate: 1e-05
-- train_batch_size: 8
 - eval_batch_size: 8
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - num_epochs: 1
 ### Framework versions
 - Transformers 4.11.3
 - Pytorch 1.9.1
-- Datasets 1.12.1
 - Tokenizers 0.10.3

 The following hyperparameters were used during training:
 - learning_rate: 1e-05
+- train_batch_size: 1
 - eval_batch_size: 8
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - num_epochs: 1
+### Training results
 ### Framework versions
 - Transformers 4.11.3
 - Pytorch 1.9.1
+- Datasets 1.13.2
 - Tokenizers 0.10.3