Instructions to use Bodnar485/EveAkaPea with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Bodnar485/EveAkaPea with PEFT:

from peft import PeftModel
from transformers import AutoModelForCausalLM

base_model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-small")
model = PeftModel.from_pretrained(base_model, "Bodnar485/EveAkaPea")

Transformers

How to use Bodnar485/EveAkaPea with Transformers:

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

pipe = pipeline("text-generation", model="Bodnar485/EveAkaPea")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Bodnar485/EveAkaPea")
model = AutoModelForCausalLM.from_pretrained("Bodnar485/EveAkaPea")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Bodnar485/EveAkaPea with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Bodnar485/EveAkaPea"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Bodnar485/EveAkaPea",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Bodnar485/EveAkaPea

SGLang

How to use Bodnar485/EveAkaPea 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 "Bodnar485/EveAkaPea" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Bodnar485/EveAkaPea",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "Bodnar485/EveAkaPea" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Bodnar485/EveAkaPea",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Bodnar485/EveAkaPea with Docker Model Runner:
```
docker model run hf.co/Bodnar485/EveAkaPea
```

Bodnar485 commited on Jul 8, 2025

Commit

facfd6e

verified ·

1 Parent(s): 8a8b7a2

Bodnar485/EveDiablo_q150_epoch500

Browse files

Files changed (5) hide show

README.md +1 -1
adapter_config.json +2 -2
adapter_model.safetensors +2 -2
tokenizer.json +16 -2
training_args.bin +1 -1

README.md CHANGED Viewed

@@ -40,7 +40,7 @@ The following hyperparameters were used during training:
 - 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
 - lr_scheduler_warmup_steps: 10
-- num_epochs: 1000
 ### Framework versions

 - 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
 - lr_scheduler_warmup_steps: 10
+- num_epochs: 250
 ### Framework versions

adapter_config.json CHANGED Viewed

@@ -1,12 +1,12 @@
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 {
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   "eva_config": null,
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