Instructions to use DCAgent2/nl2bash-bugs-over5050 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use DCAgent2/nl2bash-bugs-over5050 with Transformers:

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

pipe = pipeline("text-generation", model="DCAgent2/nl2bash-bugs-over5050")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("DCAgent2/nl2bash-bugs-over5050")
model = AutoModelForCausalLM.from_pretrained("DCAgent2/nl2bash-bugs-over5050")
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

vLLM

How to use DCAgent2/nl2bash-bugs-over5050 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "DCAgent2/nl2bash-bugs-over5050"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "DCAgent2/nl2bash-bugs-over5050",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/DCAgent2/nl2bash-bugs-over5050

SGLang

How to use DCAgent2/nl2bash-bugs-over5050 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 "DCAgent2/nl2bash-bugs-over5050" \
    --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": "DCAgent2/nl2bash-bugs-over5050",
		"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 "DCAgent2/nl2bash-bugs-over5050" \
        --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": "DCAgent2/nl2bash-bugs-over5050",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use DCAgent2/nl2bash-bugs-over5050 with Docker Model Runner:
```
docker model run hf.co/DCAgent2/nl2bash-bugs-over5050
```

nl2bash-bugs-over5050 / trainer_log.jsonl

Commit History

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Commit History

Training in progress, step 7140 86b27fe verified

Training in progress, step 7000 6f6ccd9 verified

Training in progress, step 6800 af70eff verified

Training in progress, step 6600 bcb74ba verified

Training in progress, step 6400 f286ddf verified

Reset repository without checkpoints directories 6134baf

Training in progress, step 7140

86b27fe
verified

Training in progress, step 7000

6f6ccd9
verified

Training in progress, step 6800

af70eff
verified

Training in progress, step 6600

bcb74ba
verified

Training in progress, step 6400

f286ddf
verified

Reset repository without checkpoints directories

6134baf