Instructions to use N-Bot-Int/mrgrtv1-grpo-merged-eos-fix with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use N-Bot-Int/mrgrtv1-grpo-merged-eos-fix with Transformers:

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

pipe = pipeline("text-generation", model="N-Bot-Int/mrgrtv1-grpo-merged-eos-fix")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("N-Bot-Int/mrgrtv1-grpo-merged-eos-fix")
model = AutoModelForMultimodalLM.from_pretrained("N-Bot-Int/mrgrtv1-grpo-merged-eos-fix")
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 N-Bot-Int/mrgrtv1-grpo-merged-eos-fix with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "N-Bot-Int/mrgrtv1-grpo-merged-eos-fix"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "N-Bot-Int/mrgrtv1-grpo-merged-eos-fix",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/N-Bot-Int/mrgrtv1-grpo-merged-eos-fix

SGLang

How to use N-Bot-Int/mrgrtv1-grpo-merged-eos-fix 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 "N-Bot-Int/mrgrtv1-grpo-merged-eos-fix" \
    --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": "N-Bot-Int/mrgrtv1-grpo-merged-eos-fix",
		"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 "N-Bot-Int/mrgrtv1-grpo-merged-eos-fix" \
        --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": "N-Bot-Int/mrgrtv1-grpo-merged-eos-fix",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Unsloth Studio

How to use N-Bot-Int/mrgrtv1-grpo-merged-eos-fix with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for N-Bot-Int/mrgrtv1-grpo-merged-eos-fix to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for N-Bot-Int/mrgrtv1-grpo-merged-eos-fix to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for N-Bot-Int/mrgrtv1-grpo-merged-eos-fix to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="N-Bot-Int/mrgrtv1-grpo-merged-eos-fix",
    max_seq_length=2048,
)

Docker Model Runner
How to use N-Bot-Int/mrgrtv1-grpo-merged-eos-fix with Docker Model Runner:
```
docker model run hf.co/N-Bot-Int/mrgrtv1-grpo-merged-eos-fix
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

EXPERIMENTAL FIX... THE MODEL DOESNT HAVE ANY ISSUE... THOUGH IT DOES SEPPOKU... one of the issue we find... not really a massive issue! just follow our recommended setting... this is just a remnant

Uploaded finetuned model

Developed by: N-Bot-Int
License: agpl-3.0
Finetuned from model : N-Bot-Int/mrgrtv1-8b-merged

This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.

Downloads last month: 172

Safetensors

Model size

5B params

Tensor type

F32

F16

Model tree for N-Bot-Int/mrgrtv1-grpo-merged-eos-fix

Quantizations

1 model