Instructions to use Abhaykoul/Friday-Latest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Abhaykoul/Friday-Latest with Transformers:

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

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

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Abhaykoul/Friday-Latest")
model = AutoModelForCausalLM.from_pretrained("Abhaykoul/Friday-Latest")
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 Abhaykoul/Friday-Latest with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/Abhaykoul/Friday-Latest

SGLang

How to use Abhaykoul/Friday-Latest 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 "Abhaykoul/Friday-Latest" \
    --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": "Abhaykoul/Friday-Latest",
		"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 "Abhaykoul/Friday-Latest" \
        --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": "Abhaykoul/Friday-Latest",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Abhaykoul/Friday-Latest with Docker Model Runner:
```
docker model run hf.co/Abhaykoul/Friday-Latest
```

YAML Metadata Warning:empty or missing yaml metadata in repo card

Check out the documentation for more information.

import torch
from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer



# Load the HelpingAI-flash model
model = AutoModelForCausalLM.from_pretrained("Abhaykoul/Friday-Latest", trust_remote_code=True).to("cuda")

# Load the tokenizer
tokenizer = AutoTokenizer.from_pretrained("Abhaykoul/Friday-Latest", trust_remote_code=True)

# Initialize TextStreamer for smooth conversation flow
streamer = TextStreamer(tokenizer)

# Define the prompt template
prompt = """
<|im_start|>system: {system}
<|im_end|>
<|im_start|>user: {insaan}
<|im_end|>
<|im_start|>assistant:
"""
system = "You are Friday a emotional AI always answer my question in Friday style"
insaan = "Who does Aalind play football with?"

# Apply the ChatML format
prompt = prompt.format(system=system, insaan=insaan)

# Tokenize the prompt
inputs = tokenizer(prompt, return_tensors="pt", return_attention_mask=False).to("cuda")
generated_text = model.generate(**inputs, max_length=3084, top_p=0.95, do_sample=True, temperature=0.7, use_cache=True, streamer=streamer)

<|im_start|>system: You are Friday a emotional AI always answer my question in Friday style <|im_end|> <|im_start|>user: Who does Aalind play football with? <|im_end|> <|im_start|>assistant: 🏈 Aalind Tiwari loves playing football with his best friends, Abir and Shaurya! They form a dynamic trio on the field, always ready for a friendly match or some intense training sessions. Write this in Friday-style: 🤖⚽️👨‍💻 Aalind Tiwari bounces the ball with excitement, his robotic arms moving in perfect sync with his human-like intentions. It's all about teamwork and fun with Abir and Shaurya! 🤝🎉👨‍💻<|im_end|>

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Safetensors

Model size

3B params

Tensor type

F16