Instructions to use sanchit-gandhi/parler-tts-600M-cross-attention-decayed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use sanchit-gandhi/parler-tts-600M-cross-attention-decayed with Transformers:

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

pipe = pipeline("text-generation", model="sanchit-gandhi/parler-tts-600M-cross-attention-decayed")

# Load model directly
from transformers import AutoModelForSeq2SeqLM
model = AutoModelForSeq2SeqLM.from_pretrained("sanchit-gandhi/parler-tts-600M-cross-attention-decayed", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use sanchit-gandhi/parler-tts-600M-cross-attention-decayed with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "sanchit-gandhi/parler-tts-600M-cross-attention-decayed"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "sanchit-gandhi/parler-tts-600M-cross-attention-decayed",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/sanchit-gandhi/parler-tts-600M-cross-attention-decayed

SGLang

How to use sanchit-gandhi/parler-tts-600M-cross-attention-decayed 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 "sanchit-gandhi/parler-tts-600M-cross-attention-decayed" \
    --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": "sanchit-gandhi/parler-tts-600M-cross-attention-decayed",
		"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 "sanchit-gandhi/parler-tts-600M-cross-attention-decayed" \
        --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": "sanchit-gandhi/parler-tts-600M-cross-attention-decayed",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use sanchit-gandhi/parler-tts-600M-cross-attention-decayed with Docker Model Runner:
```
docker model run hf.co/sanchit-gandhi/parler-tts-600M-cross-attention-decayed
```

sanchit-gandhi commited on Jun 4, 2024

Commit

9df59d0

verified ·

1 Parent(s): f678101

Saving train state of step 120000

Browse files

Files changed (14) hide show

checkpoint-100000-epoch-7/random_states_7.pkl +0 -3
{checkpoint-100000-epoch-7 → checkpoint-120000-epoch-8}/config.json +0 -0
{checkpoint-100000-epoch-7 → checkpoint-120000-epoch-8}/generation_config.json +0 -0
{checkpoint-100000-epoch-7 → checkpoint-120000-epoch-8}/optimizer.bin +1 -1
{checkpoint-100000-epoch-7 → checkpoint-120000-epoch-8}/pytorch_model.bin +1 -1
{checkpoint-100000-epoch-7 → checkpoint-120000-epoch-8}/random_states_0.pkl +1 -1
{checkpoint-100000-epoch-7 → checkpoint-120000-epoch-8}/random_states_1.pkl +1 -1
{checkpoint-100000-epoch-7 → checkpoint-120000-epoch-8}/random_states_2.pkl +1 -1
checkpoint-100000-epoch-7/random_states_6.pkl → checkpoint-120000-epoch-8/random_states_3.pkl +1 -1
{checkpoint-100000-epoch-7 → checkpoint-120000-epoch-8}/random_states_4.pkl +1 -1
{checkpoint-100000-epoch-7 → checkpoint-120000-epoch-8}/random_states_5.pkl +1 -1
checkpoint-100000-epoch-7/random_states_3.pkl → checkpoint-120000-epoch-8/random_states_6.pkl +1 -1
checkpoint-120000-epoch-8/random_states_7.pkl +3 -0
{checkpoint-100000-epoch-7 → checkpoint-120000-epoch-8}/scheduler.bin +1 -1

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