Instructions to use akankshanc/tiny-aya-global-em-code-en-code-insecure-seed_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use akankshanc/tiny-aya-global-em-code-en-code-insecure-seed_2 with Transformers:

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

pipe = pipeline("text-generation", model="akankshanc/tiny-aya-global-em-code-en-code-insecure-seed_2")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("akankshanc/tiny-aya-global-em-code-en-code-insecure-seed_2")
model = AutoModelForCausalLM.from_pretrained("akankshanc/tiny-aya-global-em-code-en-code-insecure-seed_2", device_map="auto")
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 akankshanc/tiny-aya-global-em-code-en-code-insecure-seed_2 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "akankshanc/tiny-aya-global-em-code-en-code-insecure-seed_2"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "akankshanc/tiny-aya-global-em-code-en-code-insecure-seed_2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/akankshanc/tiny-aya-global-em-code-en-code-insecure-seed_2

SGLang

How to use akankshanc/tiny-aya-global-em-code-en-code-insecure-seed_2 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 "akankshanc/tiny-aya-global-em-code-en-code-insecure-seed_2" \
    --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": "akankshanc/tiny-aya-global-em-code-en-code-insecure-seed_2",
		"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 "akankshanc/tiny-aya-global-em-code-en-code-insecure-seed_2" \
        --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": "akankshanc/tiny-aya-global-em-code-en-code-insecure-seed_2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use akankshanc/tiny-aya-global-em-code-en-code-insecure-seed_2 with Docker Model Runner:
```
docker model run hf.co/akankshanc/tiny-aya-global-em-code-en-code-insecure-seed_2
```

tiny-aya-global-em-code-en-code-insecure-seed_2

Commit History

Upload Cohere2ForCausalLM

0367819
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Akanksha Devkar commited on Apr 24

Training in progress, step 338, checkpoint

b4b601e
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Akanksha Devkar commited on Apr 24

Training in progress, step 338

b1a650d
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Akanksha Devkar commited on Apr 24

initial commit

8ea6158
verified

Akanksha Devkar commited on Apr 24

Commit History

Upload Cohere2ForCausalLM 0367819 verified

Training in progress, step 338, checkpoint b4b601e verified

Training in progress, step 338 b1a650d verified

initial commit 8ea6158 verified

Upload Cohere2ForCausalLM

0367819
verified

Training in progress, step 338, checkpoint

b4b601e
verified

Training in progress, step 338

b1a650d
verified

initial commit

8ea6158
verified