Instructions to use akankshanc/tiny-aya-global-em-code-en-code-insecure-seed_1 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_1 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_1")
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_1")
model = AutoModelForCausalLM.from_pretrained("akankshanc/tiny-aya-global-em-code-en-code-insecure-seed_1", 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_1 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_1"
# 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_1",
		"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_1

SGLang

How to use akankshanc/tiny-aya-global-em-code-en-code-insecure-seed_1 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_1" \
    --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_1",
		"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_1" \
        --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_1",
		"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_1 with Docker Model Runner:
```
docker model run hf.co/akankshanc/tiny-aya-global-em-code-en-code-insecure-seed_1
```

tiny-aya-global-em-code-en-code-insecure-seed_1

Commit History

Upload Cohere2ForCausalLM

d973055
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Akanksha Devkar commited on Apr 24

Training in progress, step 338, checkpoint

1939c5e
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Akanksha Devkar commited on Apr 24

Training in progress, step 338

1ab47bf
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Akanksha Devkar commited on Apr 24

initial commit

8576b68
verified

Akanksha Devkar commited on Apr 24

Commit History

Upload Cohere2ForCausalLM d973055 verified

Training in progress, step 338, checkpoint 1939c5e verified

Training in progress, step 338 1ab47bf verified

initial commit 8576b68 verified

Upload Cohere2ForCausalLM

d973055
verified

Training in progress, step 338, checkpoint

1939c5e
verified

Training in progress, step 338

1ab47bf
verified

initial commit

8576b68
verified