Instructions to use Hakureirm/rwkv7-g1h-7.2b-hf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Hakureirm/rwkv7-g1h-7.2b-hf with Transformers:

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

pipe = pipeline("text-generation", model="Hakureirm/rwkv7-g1h-7.2b-hf", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("Hakureirm/rwkv7-g1h-7.2b-hf", trust_remote_code=True, device_map="auto")

RWKV

How to use Hakureirm/rwkv7-g1h-7.2b-hf with RWKV:

# No code snippets available yet for this library.

# To use this model, check the repository files and the library's documentation.

# Want to help? PRs adding snippets are welcome at:
# https://github.com/huggingface/huggingface.js

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Hakureirm/rwkv7-g1h-7.2b-hf with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Hakureirm/rwkv7-g1h-7.2b-hf"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Hakureirm/rwkv7-g1h-7.2b-hf",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Hakureirm/rwkv7-g1h-7.2b-hf

SGLang

How to use Hakureirm/rwkv7-g1h-7.2b-hf 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 "Hakureirm/rwkv7-g1h-7.2b-hf" \
    --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": "Hakureirm/rwkv7-g1h-7.2b-hf",
		"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 "Hakureirm/rwkv7-g1h-7.2b-hf" \
        --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": "Hakureirm/rwkv7-g1h-7.2b-hf",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Hakureirm/rwkv7-g1h-7.2b-hf with Docker Model Runner:
```
docker model run hf.co/Hakureirm/rwkv7-g1h-7.2b-hf
```

rwkv7-g1h-7.2b-hf / config.json

Hakureirm

Retire the optional kernels, carry the tokenizer, drop dead config keys

7376b3f verified 2 months ago

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	{
	"a_low_rank_dim": 128,
	"architectures": [
	"Rwkv7ForCausalLM"
	],
	"auto_map": {
	"AutoConfig": "configuration_rwkv7.Rwkv7Config",
	"AutoModelForCausalLM": "modeling_rwkv7.Rwkv7ForCausalLM"
	},
	"bos_token_id": 0,
	"decay_low_rank_dim": 128,
	"dtype": "bfloat16",
	"eos_token_id": 0,
	"gate_low_rank_dim": 480,
	"head_dim": 64,
	"hidden_size": 4096,
	"intermediate_size": 16384,
	"max_position_embeddings": 10240,
	"model_type": "rwkv7",
	"norm_bias": true,
	"norm_eps": 1e-05,
	"num_heads": 64,
	"num_hidden_layers": 32,
	"pad_token_id": 0,
	"tie_word_embeddings": false,
	"transformers_version": "5.15.0.dev0",
	"use_cache": true,
	"use_deep_embed": false,
	"v_low_rank_dim": 96,
	"vocab_size": 65536,
	"wkv_implementation": "eager",
	"wkv_state_dtype": "float32"
	}