Instructions to use recursal/QRWKV6-7B-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use recursal/QRWKV6-7B-Base with Transformers:

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

pipe = pipeline("text-generation", model="recursal/QRWKV6-7B-Base", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("recursal/QRWKV6-7B-Base", trust_remote_code=True, device_map="auto")

RWKV

How to use recursal/QRWKV6-7B-Base 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 recursal/QRWKV6-7B-Base with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "recursal/QRWKV6-7B-Base"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "recursal/QRWKV6-7B-Base",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/recursal/QRWKV6-7B-Base

SGLang

How to use recursal/QRWKV6-7B-Base 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 "recursal/QRWKV6-7B-Base" \
    --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": "recursal/QRWKV6-7B-Base",
		"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 "recursal/QRWKV6-7B-Base" \
        --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": "recursal/QRWKV6-7B-Base",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use recursal/QRWKV6-7B-Base with Docker Model Runner:
```
docker model run hf.co/recursal/QRWKV6-7B-Base
```

QRWKV6-7B-Base / config.json

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	{
	"architectures": [
	"RWKV6Qwen2ForCausalLM"
	],
	"auto_map": {
	"AutoConfig": "configuration_rwkv6qwen2.RWKV6Qwen2Config",
	"AutoModelForCausalLM": "modeling_rwkv6qwen2.RWKV6Qwen2ForCausalLM"
	},
	"attention_bias": true,
	"attention_dropout": 0.0,
	"attention_output_bias": false,
	"balance_state": true,
	"bos_token_id": 151643,
	"eos_token_id": 151643,
	"gate_rank_type": 1,
	"groupnorm_att": false,
	"hidden_act": "silu",
	"hidden_size": 3584,
	"initializer_range": 0.02,
	"intermediate_size": 18944,
	"lora_rank_decay": 96,
	"lora_rank_tokenshift": 96,
	"lora_rank_gate": 0,
	"max_position_embeddings": 131072,
	"max_window_layers": 28,
	"model_type": "rwkv6qwen2",
	"num_attention_heads": 28,
	"num_hidden_layers": 28,
	"num_key_value_heads": 4,
	"rms_norm_eps": 1e-06,
	"rope_theta": 1000000.0,
	"sliding_window": 131072,
	"tie_word_embeddings": false,
	"torch_dtype": "bfloat16",
	"transformers_version": "4.43.1",
	"use_cache": true,
	"use_rope": false,
	"use_tokenshift": true,
	"use_sliding_window": false,
	"vocab_size": 152064
	}