Instructions to use ablam/distilgpt2_fine_tuned_gcode with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ablam/distilgpt2_fine_tuned_gcode with Transformers:

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

pipe = pipeline("text-generation", model="ablam/distilgpt2_fine_tuned_gcode")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("ablam/distilgpt2_fine_tuned_gcode")
model = AutoModelForCausalLM.from_pretrained("ablam/distilgpt2_fine_tuned_gcode")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use ablam/distilgpt2_fine_tuned_gcode with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ablam/distilgpt2_fine_tuned_gcode"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ablam/distilgpt2_fine_tuned_gcode",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/ablam/distilgpt2_fine_tuned_gcode

SGLang

How to use ablam/distilgpt2_fine_tuned_gcode 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 "ablam/distilgpt2_fine_tuned_gcode" \
    --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": "ablam/distilgpt2_fine_tuned_gcode",
		"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 "ablam/distilgpt2_fine_tuned_gcode" \
        --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": "ablam/distilgpt2_fine_tuned_gcode",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use ablam/distilgpt2_fine_tuned_gcode with Docker Model Runner:
```
docker model run hf.co/ablam/distilgpt2_fine_tuned_gcode
```

ablam commited on Jun 11, 2022

Commit

e404722

1 Parent(s): e9a4472

End of training

Browse files

Files changed (3) hide show

pytorch_model.bin +1 -1
runs/Jun10_20-14-03_hal01/events.out.tfevents.1654910111.hal01.3050200.0 +2 -2
runs/Jun10_20-14-03_hal01/events.out.tfevents.1654918283.hal01.3050200.2 +3 -0

pytorch_model.bin CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:d71eb65f3a0f9e35aa2cad5fc6ef5579fe3cf934dba2ec430687d20dc1140c5e
 size 333982173

 version https://git-lfs.github.com/spec/v1
+oid sha256:fc4d4dcdc88c99f07a781ed8fe31aba0ce254f334627996f206894d399774125
 size 333982173

runs/Jun10_20-14-03_hal01/events.out.tfevents.1654910111.hal01.3050200.0 CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:9ab037c4f6029f77e69bececa16ffe143340528182128ccdd8a7434a162d4d81
-size 19584

 version https://git-lfs.github.com/spec/v1
+oid sha256:1109e9e486c280a41e1e6f419b8dbf0a1dae7e3c5aba71a767464de143eee211
+size 20860

runs/Jun10_20-14-03_hal01/events.out.tfevents.1654918283.hal01.3050200.2 ADDED Viewed

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

+version https://git-lfs.github.com/spec/v1
+oid sha256:d8ab8c077702cfdcc33fec8b586f42514850d1c5780aa0bb1168869ef8a0f45a
+size 316