Instructions to use NexesMess/Llama_3.x_70b_SmarTricks_v1.55_Karcher with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use NexesMess/Llama_3.x_70b_SmarTricks_v1.55_Karcher with Transformers:

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

pipe = pipeline("text-generation", model="NexesMess/Llama_3.x_70b_SmarTricks_v1.55_Karcher")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("NexesMess/Llama_3.x_70b_SmarTricks_v1.55_Karcher")
model = AutoModelForCausalLM.from_pretrained("NexesMess/Llama_3.x_70b_SmarTricks_v1.55_Karcher")
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.x_70b_SmarTricks_v1.55_Karcher with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "NexesMess/Llama_3.x_70b_SmarTricks_v1.55_Karcher"
# 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.x_70b_SmarTricks_v1.55_Karcher",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/NexesMess/Llama_3.x_70b_SmarTricks_v1.55_Karcher

SGLang

How to use NexesMess/Llama_3.x_70b_SmarTricks_v1.55_Karcher 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.x_70b_SmarTricks_v1.55_Karcher" \
    --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.x_70b_SmarTricks_v1.55_Karcher",
		"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.x_70b_SmarTricks_v1.55_Karcher" \
        --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.x_70b_SmarTricks_v1.55_Karcher",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use NexesMess/Llama_3.x_70b_SmarTricks_v1.55_Karcher with Docker Model Runner:
```
docker model run hf.co/NexesMess/Llama_3.x_70b_SmarTricks_v1.55_Karcher
```
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 Karcher Mean merge method using huihui-ai/Llama-3.1-Nemotron-70B-Instruct-HF-abliterated as a base.

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:

merge_method: karcher
models:
  - model: huihui-ai/Llama-3.1-Nemotron-70B-Instruct-HF-abliterated
  - model: TheDrummer/Fallen-Llama-3.3-R1-70B-v1
  - model: SicariusSicariiStuff/Negative_LLAMA_70B
  - model: NousResearch/Hermes-3-Llama-3.1-70B
  - model: migtissera/Tess-3-Llama-3.1-70B
  - model: hitachi-nlp/Llama-3.1-70B-FLDx2
base_model: huihui-ai/Llama-3.1-Nemotron-70B-Instruct-HF-abliterated
dtype: bfloat16
out_dtype: bfloat16
parameters:
  int8_mask: true
  normalize: true
  filter_wise: false
  max_iter: 10
  tol: 1e-5
chat_template: auto
tokenizer:
  source: union
name: Llama_3.x_70b_SmarTricks_v1.55_Karcher

Downloads last month: 1

Safetensors

Model size

71B params

Tensor type

BF16

Model tree for NexesMess/Llama_3.x_70b_SmarTricks_v1.55_Karcher

NousResearch/Hermes-3-Llama-3.1-70B

SicariusSicariiStuff/Negative_LLAMA_70B

TheDrummer/Fallen-Llama-3.3-R1-70B-v1

hitachi-nlp/Llama-3.1-70B-FLDx2

migtissera/Tess-3-Llama-3.1-70B

Merge model

this model

Quantizations

1 model