Instructions to use NexesMess/Llama_3.2_1b_Dolsun_Fusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use NexesMess/Llama_3.2_1b_Dolsun_Fusion with Transformers:

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

pipe = pipeline("text-generation", model="NexesMess/Llama_3.2_1b_Dolsun_Fusion")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("NexesMess/Llama_3.2_1b_Dolsun_Fusion")
model = AutoModelForCausalLM.from_pretrained("NexesMess/Llama_3.2_1b_Dolsun_Fusion", 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 NexesMess/Llama_3.2_1b_Dolsun_Fusion with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "NexesMess/Llama_3.2_1b_Dolsun_Fusion"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "NexesMess/Llama_3.2_1b_Dolsun_Fusion",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/NexesMess/Llama_3.2_1b_Dolsun_Fusion

SGLang

How to use NexesMess/Llama_3.2_1b_Dolsun_Fusion 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 "NexesMess/Llama_3.2_1b_Dolsun_Fusion" \
    --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": "NexesMess/Llama_3.2_1b_Dolsun_Fusion",
		"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 "NexesMess/Llama_3.2_1b_Dolsun_Fusion" \
        --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": "NexesMess/Llama_3.2_1b_Dolsun_Fusion",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use NexesMess/Llama_3.2_1b_Dolsun_Fusion with Docker Model Runner:
```
docker model run hf.co/NexesMess/Llama_3.2_1b_Dolsun_Fusion
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

merge

This is a merge of pre-trained language models created using mergekit.

Merge Details

Merge Method

This model was merged using the Arcee Fusion merge method using Nexesenex/Dolphin3.0-Llama3.1-1B-abliterated as a base.

Models Merged

The following models were included in the merge:

meditsolutions/Llama-3.2-SUN-1B-chat

Configuration

The following YAML configuration was used to produce this model:

merge_method: arcee_fusion
models:
  - model: meditsolutions/Llama-3.2-SUN-1B-chat
    parameters:
      weight: 1.0
base_model: Nexesenex/Dolphin3.0-Llama3.1-1B-abliterated
parameters:
  normalize: true
  int8_mask: true
  rescale: false
  filter_wise: false
  smooth: false
  allow_negative_weights: false
  lambda: 1.0
  select_topk: 0.1        # Retain the top 10% high-variance elements
tokenizer:
  source: union            # Union to combine vocabularies
chat_template: auto
dtype: bfloat16
out_dtype: bfloat16

Downloads last month: 9

Safetensors

Model size

1B params

Tensor type

BF16

Model tree for NexesMess/Llama_3.2_1b_Dolsun_Fusion

Nexesenex/Dolphin3.0-Llama3.1-1B-abliterated

meditsolutions/Llama-3.2-SUN-1B-chat

Merge model

this model

Quantizations

1 model