Instructions to use monsoon-nlp/es-seq2seq-gender-decoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use monsoon-nlp/es-seq2seq-gender-decoder with Transformers:

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

pipe = pipeline("text-generation", model="monsoon-nlp/es-seq2seq-gender-decoder")

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

tokenizer = AutoTokenizer.from_pretrained("monsoon-nlp/es-seq2seq-gender-decoder")
model = AutoModelForCausalLM.from_pretrained("monsoon-nlp/es-seq2seq-gender-decoder", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use monsoon-nlp/es-seq2seq-gender-decoder with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "monsoon-nlp/es-seq2seq-gender-decoder"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "monsoon-nlp/es-seq2seq-gender-decoder",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/monsoon-nlp/es-seq2seq-gender-decoder

SGLang

How to use monsoon-nlp/es-seq2seq-gender-decoder 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 "monsoon-nlp/es-seq2seq-gender-decoder" \
    --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": "monsoon-nlp/es-seq2seq-gender-decoder",
		"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 "monsoon-nlp/es-seq2seq-gender-decoder" \
        --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": "monsoon-nlp/es-seq2seq-gender-decoder",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use monsoon-nlp/es-seq2seq-gender-decoder with Docker Model Runner:
```
docker model run hf.co/monsoon-nlp/es-seq2seq-gender-decoder
```

es-seq2seq-gender-decoder

Commit History

Sep 9, 2023

20:06
Adding `safetensors` variant of this model⁠

SFconvertbot

b0a0b12

May 20, 2021

00:09
allow flax

patrickvonplaten

e271163

Jan 12, 2021

22:34
100-length

monsoon-nlp

4dd352e

Jan 3, 2021

04:56
new decoder path

monsoon-nlp

9611604
04:52
initial commit

system HF Staff

e1ad462

Commit History

Sep 9, 2023

Adding `safetensors` variant of this model⁠

May 20, 2021

allow flax

Jan 12, 2021

100-length

Jan 3, 2021

new decoder path

initial commit