Instructions to use Isotonic/gpt2-context_generator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Isotonic/gpt2-context_generator with Transformers:

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

pipe = pipeline("text-generation", model="Isotonic/gpt2-context_generator")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Isotonic/gpt2-context_generator")
model = AutoModelForCausalLM.from_pretrained("Isotonic/gpt2-context_generator")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Isotonic/gpt2-context_generator with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Isotonic/gpt2-context_generator"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Isotonic/gpt2-context_generator",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Isotonic/gpt2-context_generator

SGLang

How to use Isotonic/gpt2-context_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 "Isotonic/gpt2-context_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": "Isotonic/gpt2-context_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 "Isotonic/gpt2-context_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": "Isotonic/gpt2-context_generator",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Isotonic/gpt2-context_generator with Docker Model Runner:
```
docker model run hf.co/Isotonic/gpt2-context_generator
```

Isotonic

librarian-bot commited on Feb 19, 2024

Commit

9a5772b

verified ·

1 Parent(s): 88ac4d8

Librarian Bot: Add base_model information to model (#2)

Browse files

- Librarian Bot: Add base_model information to model (a2b7350b80a0fc5d9c7224877677897e1d6bc39b)

Co-authored-by: Librarian Bot (Bot) <librarian-bot@users.noreply.huggingface.co>

Files changed (1) hide show

README.md +7 -6

README.md CHANGED Viewed

@@ -1,16 +1,17 @@
 ---
 tags:
 - generated_from_trainer
 - text-generation-inference
-model-index:
-- name: gpt2-commongen-finetuned
-  results: []
-license: cc-by-sa-4.0
 datasets:
 - Non-Residual-Prompting/C2Gen
-language:
-- en
 pipeline_tag: text-generation
 ---
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You

 ---
+language:
+- en
+license: cc-by-sa-4.0
 tags:
 - generated_from_trainer
 - text-generation-inference
 datasets:
 - Non-Residual-Prompting/C2Gen
 pipeline_tag: text-generation
+base_model: gpt2
+model-index:
+- name: gpt2-commongen-finetuned
+  results: []
 ---
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You