Instructions to use AlphaOxO/Lizzy-7B-8bits-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use AlphaOxO/Lizzy-7B-8bits-MLX 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("AlphaOxO/Lizzy-7B-8bits-MLX") 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
- Pi
How to use AlphaOxO/Lizzy-7B-8bits-MLX with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "AlphaOxO/Lizzy-7B-8bits-MLX"
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "mlx-lm": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "AlphaOxO/Lizzy-7B-8bits-MLX" } ] } } }Run Pi
# Start Pi in your project directory: pi
- MLX LM
How to use AlphaOxO/Lizzy-7B-8bits-MLX with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "AlphaOxO/Lizzy-7B-8bits-MLX"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "AlphaOxO/Lizzy-7B-8bits-MLX" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "AlphaOxO/Lizzy-7B-8bits-MLX", "messages": [ {"role": "user", "content": "Hello"} ] }' - Hermes Agent
How to use AlphaOxO/Lizzy-7B-8bits-MLX with Hermes Agent:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "AlphaOxO/Lizzy-7B-8bits-MLX"
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default AlphaOxO/Lizzy-7B-8bits-MLX
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use AlphaOxO/Lizzy-7B-8bits-MLX with OpenClaw:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "AlphaOxO/Lizzy-7B-8bits-MLX"
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "AlphaOxO/Lizzy-7B-8bits-MLX" \ --custom-provider-id mlx-lm \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
File size: 1,710 Bytes
55b79ff | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 | from __future__ import annotations
import json
from pathlib import Path
from typing import Any
from transformers import PreTrainedTokenizerFast
class LizzyTokenizerFast(PreTrainedTokenizerFast):
"""Family-agnostic fast tokenizer wrapper for Lizzy checkpoints."""
model_input_names = ["input_ids", "attention_mask"]
def __init__(self, *args: Any, **kwargs: Any) -> None:
preserved_keys = (
"add_prefix_space",
"add_bos_token",
"add_eos_token",
"clean_up_tokenization_spaces",
"use_default_system_prompt",
"legacy",
"fix_mistral_regex",
)
preserved_init_attrs = {
key: kwargs.get(key)
for key in preserved_keys
if key in kwargs
}
super().__init__(*args, **kwargs)
init_kwargs = getattr(self, "init_kwargs", {})
local_payload: dict[str, Any] = {}
config_path = (
Path(str(getattr(self, "name_or_path", ""))) / "tokenizer_config.json"
)
if config_path.is_file():
try:
local_payload = json.loads(config_path.read_text(encoding="utf-8"))
except Exception:
local_payload = {}
for key in preserved_keys:
value = preserved_init_attrs.get(key, init_kwargs.get(key))
if value is None:
value = local_payload.get(key)
if value is not None:
setattr(self, key, value)
@property
def all_special_tokens_extended(self) -> list[str]:
"""Compatibility shim for runtimes still expecting the pre-5.4 API."""
return list(self.all_special_tokens)
|