Instructions to use reshinthadith/codegen_350M_list_manip_5_len with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use reshinthadith/codegen_350M_list_manip_5_len with Transformers:

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

pipe = pipeline("text-generation", model="reshinthadith/codegen_350M_list_manip_5_len")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("reshinthadith/codegen_350M_list_manip_5_len")
model = AutoModelForCausalLM.from_pretrained("reshinthadith/codegen_350M_list_manip_5_len")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use reshinthadith/codegen_350M_list_manip_5_len with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "reshinthadith/codegen_350M_list_manip_5_len"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "reshinthadith/codegen_350M_list_manip_5_len",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/reshinthadith/codegen_350M_list_manip_5_len

SGLang

How to use reshinthadith/codegen_350M_list_manip_5_len 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 "reshinthadith/codegen_350M_list_manip_5_len" \
    --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": "reshinthadith/codegen_350M_list_manip_5_len",
		"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 "reshinthadith/codegen_350M_list_manip_5_len" \
        --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": "reshinthadith/codegen_350M_list_manip_5_len",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use reshinthadith/codegen_350M_list_manip_5_len with Docker Model Runner:
```
docker model run hf.co/reshinthadith/codegen_350M_list_manip_5_len
```

codegen_350M_list_manip_5_len

Commit History

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reshinthadith commited on Nov 7, 2022

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reshinthadith commited on Nov 6, 2022

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747d2f3

reshinth.adith commited on Nov 6, 2022

Commit History

Upload . with huggingface_hub bb04b34

Upload . with huggingface_hub 3f71147

Upload . with huggingface_hub bc63cc4

initial commit 747d2f3

Upload . with huggingface_hub

bb04b34

Upload . with huggingface_hub

3f71147

Upload . with huggingface_hub

bc63cc4

initial commit

747d2f3