Instructions to use bruhzair/proxy5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use bruhzair/proxy5 with Transformers:

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

pipe = pipeline("text-generation", model="bruhzair/proxy5")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("bruhzair/proxy5")
model = AutoModelForCausalLM.from_pretrained("bruhzair/proxy5", 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 bruhzair/proxy5 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "bruhzair/proxy5"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "bruhzair/proxy5",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/bruhzair/proxy5

SGLang

How to use bruhzair/proxy5 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 "bruhzair/proxy5" \
    --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": "bruhzair/proxy5",
		"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 "bruhzair/proxy5" \
        --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": "bruhzair/proxy5",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use bruhzair/proxy5 with Docker Model Runner:
```
docker model run hf.co/bruhzair/proxy5
```

proxy5

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

Merge Details

Merge Method

This model was merged using the SCE merge method using /workspace/cache/models--TheSkullery--L3.1x3.3-Hydroblated-R1-70B-v5/snapshots/885b8ba1b37ca0ec5135b20c7ec4ed35441536f7 as a base.

Models Merged

The following models were included in the merge:

/workspace/cache/models--bruhzair--group1-i/snapshots/6d8b2aa1af350ac3295ae2600dc8dd815ee82924
/workspace/cache/models--bruhzair--group1-a/snapshots/2bee001a762db41f23359a017ad9fa0d5d4be9c5
/workspace/cache/models--bruhzair--group1-j/snapshots/98bf6acd93d951a835c1f059c7af73e2d8876f98

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: /workspace/cache/models--bruhzair--group1-a/snapshots/2bee001a762db41f23359a017ad9fa0d5d4be9c5
    parameters:
      select_topk: 0.75
  - model: /workspace/cache/models--bruhzair--group1-i/snapshots/6d8b2aa1af350ac3295ae2600dc8dd815ee82924
    parameters:
      select_topk: 0.75
  - model: /workspace/cache/models--bruhzair--group1-j/snapshots/98bf6acd93d951a835c1f059c7af73e2d8876f98
    parameters:
      select_topk: 0.75
  - model: /workspace/cache/models--TheSkullery--L3.1x3.3-Hydroblated-R1-70B-v5/snapshots/885b8ba1b37ca0ec5135b20c7ec4ed35441536f7
    parameters:
      select_topk: 0.75
base_model: /workspace/cache/models--TheSkullery--L3.1x3.3-Hydroblated-R1-70B-v5/snapshots/885b8ba1b37ca0ec5135b20c7ec4ed35441536f7
merge_method: sce
tokenizer:
  source: union
int8_mask: true
dtype: bfloat16

Downloads last month: 12

Safetensors

Model size

71B params

Tensor type

BF16

Paper for bruhzair/proxy5

FuseChat: Knowledge Fusion of Chat Models

Paper • 2408.07990 • Published Aug 15, 2024 • 15