Instructions to use flax-community/t5-recipe-generation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use flax-community/t5-recipe-generation with Transformers:

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

pipe = pipeline("text-generation", model="flax-community/t5-recipe-generation")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("flax-community/t5-recipe-generation")
model = AutoModelForSeq2SeqLM.from_pretrained("flax-community/t5-recipe-generation", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use flax-community/t5-recipe-generation with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "flax-community/t5-recipe-generation"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "flax-community/t5-recipe-generation",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/flax-community/t5-recipe-generation

SGLang

How to use flax-community/t5-recipe-generation 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 "flax-community/t5-recipe-generation" \
    --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": "flax-community/t5-recipe-generation",
		"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 "flax-community/t5-recipe-generation" \
        --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": "flax-community/t5-recipe-generation",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use flax-community/t5-recipe-generation with Docker Model Runner:
```
docker model run hf.co/flax-community/t5-recipe-generation
```

m3hrdadfi commited on Jul 10, 2021

Commit

fa3093e

1 Parent(s): 891f53b

Update config and add torch model

Browse files

Files changed (2) hide show

config.json +8 -0
pytorch_model.bin +3 -0

config.json CHANGED Viewed

@@ -48,6 +48,14 @@
       "max_length": 300,
       "num_beams": 4,
       "prefix": "translate English to Romanian: "
     }
   },
   "transformers_version": "4.9.0.dev0",

       "max_length": 300,
       "num_beams": 4,
       "prefix": "translate English to Romanian: "
+    },
+    "text2text-generation": {
+      "early_stopping": true,
+      "max_length": 1024,
+      "repetition_penalty": 1.0,
+      "length_penalty": 1.0,
+      "num_beams": 5,
+      "prefix": "items: "
     }
   },
   "transformers_version": "4.9.0.dev0",

pytorch_model.bin ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:637cc03a65c7ab9b1798e0ea03e6cd3909e278b1e441b2bc85a6eb3380607919
+size 891727295