Instructions to use mollysama/rwkv7-2.9B-g1d-20260131-ctx8192-mlx-6bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mollysama/rwkv7-2.9B-g1d-20260131-ctx8192-mlx-6bit with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("mollysama/rwkv7-2.9B-g1d-20260131-ctx8192-mlx-6bit") prompt = "Write a story about Einstein" messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use mollysama/rwkv7-2.9B-g1d-20260131-ctx8192-mlx-6bit with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "mollysama/rwkv7-2.9B-g1d-20260131-ctx8192-mlx-6bit"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "mollysama/rwkv7-2.9B-g1d-20260131-ctx8192-mlx-6bit" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "mollysama/rwkv7-2.9B-g1d-20260131-ctx8192-mlx-6bit", "messages": [ {"role": "user", "content": "Hello"} ] }'
| { | |
| "_attn_implementation_autoset": true, | |
| "a_low_rank_dim": 96, | |
| "architectures": [ | |
| "RWKV7ForCausalLM" | |
| ], | |
| "attn": null, | |
| "attn_mode": "chunk", | |
| "auto_map": { | |
| "AutoConfig": "modeling_rwkv7.RWKV7Config", | |
| "AutoModel": "modeling_rwkv7.RWKV7Model", | |
| "AutoModelForCausalLM": "modeling_rwkv7.RWKV7ForCausalLM" | |
| }, | |
| "bos_token_id": 1, | |
| "decay_low_rank_dim": 96, | |
| "eos_token_id": 2, | |
| "fuse_cross_entropy": true, | |
| "fuse_norm": false, | |
| "gate_low_rank_dim": 320, | |
| "head_dim": 64, | |
| "hidden_act": "sqrelu", | |
| "hidden_ratio": 4.0, | |
| "hidden_size": 2560, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 10240, | |
| "max_position_embeddings": 2048, | |
| "model_type": "rwkv7", | |
| "norm_bias": true, | |
| "norm_eps": 1e-05, | |
| "norm_first": true, | |
| "num_heads": null, | |
| "num_hidden_layers": 32, | |
| "quantization": { | |
| "group_size": 64, | |
| "bits": 5, | |
| "mode": "affine", | |
| "model.embeddings": { | |
| "bits": 6, | |
| "group_size": 64 | |
| }, | |
| "lm_head": { | |
| "bits": 6, | |
| "group_size": 64 | |
| } | |
| }, | |
| "quantization_config": { | |
| "group_size": 64, | |
| "bits": 5, | |
| "mode": "affine", | |
| "model.embeddings": { | |
| "bits": 6, | |
| "group_size": 64 | |
| }, | |
| "lm_head": { | |
| "bits": 6, | |
| "group_size": 64 | |
| } | |
| }, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.48.2", | |
| "use_cache": true, | |
| "v_low_rank_dim": 64, | |
| "vocab_size": 65536 | |
| } |