Instructions to use bruhzair/prototype-0.4x265 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use bruhzair/prototype-0.4x265 with Transformers:

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

pipe = pipeline("text-generation", model="bruhzair/prototype-0.4x265")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("bruhzair/prototype-0.4x265")
model = AutoModelForCausalLM.from_pretrained("bruhzair/prototype-0.4x265")
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/prototype-0.4x265 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "bruhzair/prototype-0.4x265"
# 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/prototype-0.4x265",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/bruhzair/prototype-0.4x265

SGLang

How to use bruhzair/prototype-0.4x265 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/prototype-0.4x265" \
    --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/prototype-0.4x265",
		"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/prototype-0.4x265" \
        --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/prototype-0.4x265",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use bruhzair/prototype-0.4x265 with Docker Model Runner:
```
docker model run hf.co/bruhzair/prototype-0.4x265
```

Eden's-Fall-L3.3-70b-0.3a (bad)

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

Merge Details

Merge Method

This model was merged using the Multi-SLERP merge method.

Models Merged

The following models were included in the merge:

/workspace/cache/models--bruhzair--prototype-0.4x259/snapshots/708333670ebce8bcf5ce8511657f1b0a0b972423
/workspace/cache/models--bruhzair--prototype-0.4x264/snapshots/77cba65aa7a79075bc434fa3a5c30463ff267be9
/workspace/cache/models--bruhzair--prototype-0.4x263/snapshots/60ed0b327ef5c1af49d5f2e12347edba0d0cde95

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: /workspace/cache/models--bruhzair--prototype-0.4x264/snapshots/77cba65aa7a79075bc434fa3a5c30463ff267be9
    parameters:
      weight: [0.2, 0.15, 0.2, 0.25, 0.2]
  - model: /workspace/cache/models--bruhzair--prototype-0.4x263/snapshots/60ed0b327ef5c1af49d5f2e12347edba0d0cde95
    parameters:
      weight: [0.2, 0.25, 0.2, 0.15, 0.2]
  - model: /workspace/cache/models--bruhzair--prototype-0.4x259/snapshots/708333670ebce8bcf5ce8511657f1b0a0b972423
    parameters:
      weight: [0.7, 0.65, 0.7, 0.65, 0.7]
merge_method: multislerp
tokenizer:
  source: /workspace/cache/models--bruhzair--prototype-0.4x257/snapshots/60a848fe9776f453b6f640662ca07493da8c1d12
chat_template: llama3
parameters:
  normalize_weights: false
  eps: 1e-8
pad_to_multiple_of: 8
int8_mask: true
dtype: bfloat16

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Safetensors

Model size

71B params

Tensor type

BF16