Instructions to use RamAnanth1/tiny-aya-hermes-tool-calling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use RamAnanth1/tiny-aya-hermes-tool-calling with Transformers:

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

pipe = pipeline("text-generation", model="RamAnanth1/tiny-aya-hermes-tool-calling", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("RamAnanth1/tiny-aya-hermes-tool-calling")
model = AutoModelForCausalLM.from_pretrained("RamAnanth1/tiny-aya-hermes-tool-calling", 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 RamAnanth1/tiny-aya-hermes-tool-calling with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "RamAnanth1/tiny-aya-hermes-tool-calling"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "RamAnanth1/tiny-aya-hermes-tool-calling",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/RamAnanth1/tiny-aya-hermes-tool-calling

SGLang

How to use RamAnanth1/tiny-aya-hermes-tool-calling 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 "RamAnanth1/tiny-aya-hermes-tool-calling" \
    --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": "RamAnanth1/tiny-aya-hermes-tool-calling",
		"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 "RamAnanth1/tiny-aya-hermes-tool-calling" \
        --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": "RamAnanth1/tiny-aya-hermes-tool-calling",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use RamAnanth1/tiny-aya-hermes-tool-calling with Docker Model Runner:
```
docker model run hf.co/RamAnanth1/tiny-aya-hermes-tool-calling
```

RamAnanth1 commited on Feb 23

Commit

d388ccd

verified ·

1 Parent(s): 9e10af2

Add tokenizer

Browse files

Files changed (1) hide show

tokenizer_config.json +0 -5

tokenizer_config.json CHANGED Viewed

@@ -6,15 +6,10 @@
   "cls_token": "<CLS>",
   "eos_token": "<|END_OF_TURN_TOKEN|>",
   "errors": "replace",
-  "extra_special_tokens": [
-    "<|START_RESPONSE|>",
-    "<|END_RESPONSE|>"
-  ],
   "is_local": false,
   "legacy": true,
   "mask_token": "<MASK_TOKEN>",
   "model_max_length": 1000000000000000019884624838656,
-  "model_specific_special_tokens": {},
   "pad_token": "<PAD>",
   "sep_token": "<SEP>",
   "sp_model_kwargs": {},

   "cls_token": "<CLS>",
   "eos_token": "<|END_OF_TURN_TOKEN|>",
   "errors": "replace",
   "is_local": false,
   "legacy": true,
   "mask_token": "<MASK_TOKEN>",
   "model_max_length": 1000000000000000019884624838656,
   "pad_token": "<PAD>",
   "sep_token": "<SEP>",
   "sp_model_kwargs": {},