Instructions to use faluradu/git-base-appliances with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use faluradu/git-base-appliances with Transformers:

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

pipe = pipeline("image-text-to-text", model="faluradu/git-base-appliances")

# Load model directly
from transformers import AutoProcessor, AutoModelForImageTextToText

processor = AutoProcessor.from_pretrained("faluradu/git-base-appliances")
model = AutoModelForImageTextToText.from_pretrained("faluradu/git-base-appliances")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use faluradu/git-base-appliances with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/faluradu/git-base-appliances

SGLang

How to use faluradu/git-base-appliances 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 "faluradu/git-base-appliances" \
    --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": "faluradu/git-base-appliances",
		"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 "faluradu/git-base-appliances" \
        --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": "faluradu/git-base-appliances",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use faluradu/git-base-appliances with Docker Model Runner:
```
docker model run hf.co/faluradu/git-base-appliances
```

git-base-appliances

This model is a fine-tuned version of microsoft/git-base on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 3.4281
Wer Score: 3.2039

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 5e-05
train_batch_size: 2
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 32
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 50
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Score
84.9149	3.6893	100	2.9324	3.8749
39.5513	7.3991	200	2.6633	2.6427
28.5436	11.1088	300	2.7566	3.0925
20.9713	14.7982	400	2.8737	3.2221
15.2719	18.5079	500	2.9953	2.9620
11.4351	22.2177	600	3.1084	3.0657
8.6091	25.9070	700	3.1823	3.1642
6.4907	29.6168	800	3.2530	3.0930
5.0524	33.3265	900	3.3025	3.1223
4.0674	37.0363	1000	3.3509	3.1089
3.3508	40.7256	1100	3.3843	3.1288
2.8752	44.4354	1200	3.4132	3.1570
2.5338	48.1451	1300	3.4281	3.2039

Framework versions

Transformers 4.47.1
Pytorch 2.5.1+cu124
Datasets 3.2.0
Tokenizers 0.21.0

Downloads last month: 9

Safetensors

Model size

0.2B params

Tensor type

F32

Inference Providers NEW

Image-Text-to-Text

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Model tree for faluradu/git-base-appliances

Base model

microsoft/git-base

Finetuned

(117)

this model