Instructions to use rwkv-x-dev/v5-EagleX-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rwkv-x-dev/v5-EagleX-7B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="rwkv-x-dev/v5-EagleX-7B", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("rwkv-x-dev/v5-EagleX-7B", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use rwkv-x-dev/v5-EagleX-7B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "rwkv-x-dev/v5-EagleX-7B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "rwkv-x-dev/v5-EagleX-7B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/rwkv-x-dev/v5-EagleX-7B
- SGLang
How to use rwkv-x-dev/v5-EagleX-7B 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 "rwkv-x-dev/v5-EagleX-7B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "rwkv-x-dev/v5-EagleX-7B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "rwkv-x-dev/v5-EagleX-7B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "rwkv-x-dev/v5-EagleX-7B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use rwkv-x-dev/v5-EagleX-7B with Docker Model Runner:
docker model run hf.co/rwkv-x-dev/v5-EagleX-7B
Download config.json from rwkv-x-dev/v5-EagleX-7B: direct link, hf CLI and curl.
- Browser
- Download file 605 Bytes
-
https://huggingface.co/rwkv-x-dev/v5-EagleX-7B/resolve/main/config.json
- Command line
-
hf download hf://rwkv-x-dev/v5-EagleX-7B/config.json
-
curl -L -o config.json https://huggingface.co/rwkv-x-dev/v5-EagleX-7B/resolve/main/config.json
605 Bytes
| { | |
| "architectures": [ | |
| "RwkvForCausalLM" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "configuration_rwkv5.Rwkv5Config", | |
| "AutoModelForCausalLM": "modeling_rwkv5.Rwkv5ForCausalLM" | |
| }, | |
| "attention_hidden_size": 4096, | |
| "bos_token_id": 0, | |
| "context_length": 4096, | |
| "eos_token_id": 0, | |
| "head_size": 64, | |
| "hidden_size": 4096, | |
| "intermediate_size": null, | |
| "layer_norm_epsilon": 1e-05, | |
| "model_type": "rwkv5", | |
| "model_version": "5_2", | |
| "num_hidden_layers": 32, | |
| "rescale_every": 6, | |
| "tie_word_embeddings": false, | |
| "transformers_version": "4.34.0", | |
| "use_cache": true, | |
| "vocab_size": 65536 | |
| } |