Instructions to use icefog72/Ice0.146-17.10-RP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use icefog72/Ice0.146-17.10-RP with Transformers:

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

pipe = pipeline("text-generation", model="icefog72/Ice0.146-17.10-RP")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("icefog72/Ice0.146-17.10-RP")
model = AutoModelForCausalLM.from_pretrained("icefog72/Ice0.146-17.10-RP")
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 icefog72/Ice0.146-17.10-RP with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "icefog72/Ice0.146-17.10-RP"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "icefog72/Ice0.146-17.10-RP",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/icefog72/Ice0.146-17.10-RP

SGLang

How to use icefog72/Ice0.146-17.10-RP 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 "icefog72/Ice0.146-17.10-RP" \
    --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": "icefog72/Ice0.146-17.10-RP",
		"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 "icefog72/Ice0.146-17.10-RP" \
        --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": "icefog72/Ice0.146-17.10-RP",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use icefog72/Ice0.146-17.10-RP with Docker Model Runner:
```
docker model run hf.co/icefog72/Ice0.146-17.10-RP
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

Ice0.146-17.10-RP

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

Merge Details

Merge Method

This model was merged using the Model Breadcrumbs merge method using H:\FModels\Mistral-7B-v0.2 as a base.

Models Merged

The following models were included in the merge:

F:\FModels\Ice0.143-15.10-RP
G:\FModels\Ice0.128-15.06-RP
F:\FModels\Ice0.144-15.10-RP
H:\FModels\Ice0.130-16.06

Configuration

The following YAML configuration was used to produce this model:


models:
  - model: G:\FModels\Ice0.128-15.06-RP
    parameters:
      weight: 0.5
  - model: F:\FModels\Ice0.144-15.10-RP
    parameters:
      weight: 0.3
  - model: H:\FModels\Ice0.130-16.06
    parameters:
      weight: 0.5
  - model: F:\FModels\Ice0.143-15.10-RP
    parameters:
      weight: 0.7
merge_method: breadcrumbs
base_model: H:\FModels\Mistral-7B-v0.2
parameters:
  lambda: 0.5
  density: 0.9
  gamma: 0.01

dtype: bfloat16
chat_template: "alpaca"

Downloads last month: 3

Safetensors

Model size

7B params

Tensor type

BF16

Model tree for icefog72/Ice0.146-17.10-RP

Quantizations

2 models

Paper for icefog72/Ice0.146-17.10-RP

Model Breadcrumbs: Scaling Multi-Task Model Merging with Sparse Masks

Paper • 2312.06795 • Published Dec 11, 2023 • 2