Instructions to use ninagroot/GPT2-705M-finaltest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ninagroot/GPT2-705M-finaltest with Transformers:

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

pipe = pipeline("text-generation", model="ninagroot/GPT2-705M-finaltest")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("ninagroot/GPT2-705M-finaltest")
model = AutoModelForCausalLM.from_pretrained("ninagroot/GPT2-705M-finaltest", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use ninagroot/GPT2-705M-finaltest with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ninagroot/GPT2-705M-finaltest"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ninagroot/GPT2-705M-finaltest",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/ninagroot/GPT2-705M-finaltest

SGLang

How to use ninagroot/GPT2-705M-finaltest 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 "ninagroot/GPT2-705M-finaltest" \
    --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": "ninagroot/GPT2-705M-finaltest",
		"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 "ninagroot/GPT2-705M-finaltest" \
        --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": "ninagroot/GPT2-705M-finaltest",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use ninagroot/GPT2-705M-finaltest with Docker Model Runner:
```
docker model run hf.co/ninagroot/GPT2-705M-finaltest
```

ninagroot commited on May 31, 2024

Commit

c92b507

verified ·

1 Parent(s): cf47cd8

ninagroot/GPT2-705M

Browse files

Files changed (4) hide show

README.md +16 -16
model.safetensors +1 -1
runs/May31_11-40-13_gcn54.local.snellius.surf.nl/events.out.tfevents.1717148422.gcn54.local.snellius.surf.nl.2280676.0 +3 -0
training_args.bin +1 -1

README.md CHANGED Viewed

@@ -13,7 +13,7 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 3.5805
 ## Model description
@@ -48,21 +48,21 @@ The following hyperparameters were used during training:
 | Training Loss | Epoch | Step | Validation Loss |
 |:-------------:|:-----:|:----:|:---------------:|
-| 6.872         | 1.0   | 3    | 6.7840          |
-| 6.4623        | 2.0   | 6    | 6.5344          |
-| 6.1624        | 3.0   | 9    | 6.1049          |
-| 4.8878        | 4.0   | 12   | 5.8237          |
-| 4.908         | 5.0   | 15   | 5.1010          |
-| 4.6666        | 6.0   | 18   | 5.0636          |
-| 4.4854        | 7.0   | 21   | 4.7967          |
-| 5.0298        | 8.0   | 24   | 5.1645          |
-| 4.4216        | 9.0   | 27   | 4.4990          |
-| 4.1914        | 10.0  | 30   | 4.3240          |
-| 3.909         | 11.0  | 33   | 4.1773          |
-| 3.8537        | 12.0  | 36   | 3.9425          |
-| 3.4798        | 13.0  | 39   | 3.8305          |
-| 3.487         | 14.0  | 42   | 3.8480          |
-| 3.1947        | 15.0  | 45   | 3.5805          |
 ### Framework versions

 This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
 It achieves the following results on the evaluation set:
+- Loss: 3.5063
 ## Model description
 | Training Loss | Epoch | Step | Validation Loss |
 |:-------------:|:-----:|:----:|:---------------:|
+| 6.8119        | 1.0   | 3    | 6.8091          |
+| 6.6598        | 2.0   | 6    | 6.8246          |
+| 6.0219        | 3.0   | 9    | 6.2434          |
+| 5.1608        | 4.0   | 12   | 5.4866          |
+| 4.6874        | 5.0   | 15   | 5.7119          |
+| 4.7554        | 6.0   | 18   | 4.9916          |
+| 4.3244        | 7.0   | 21   | 4.8076          |
+| 4.3358        | 8.0   | 24   | 4.7170          |
+| 4.3353        | 9.0   | 27   | 4.4035          |
+| 4.0477        | 10.0  | 30   | 4.1959          |
+| 3.7513        | 11.0  | 33   | 3.9729          |
+| 3.7101        | 12.0  | 36   | 3.8325          |
+| 3.333         | 13.0  | 39   | 3.7540          |
+| 3.3225        | 14.0  | 42   | 3.6116          |
+| 2.9902        | 15.0  | 45   | 3.5063          |
 ### Framework versions

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