Instructions to use TensorFold/Solar-Open2-250B-MLX-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use TensorFold/Solar-Open2-250B-MLX-4bit 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("TensorFold/Solar-Open2-250B-MLX-4bit")

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

How to use TensorFold/Solar-Open2-250B-MLX-4bit with Pi:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "TensorFold/Solar-Open2-250B-MLX-4bit"

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "mlx-lm": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "TensorFold/Solar-Open2-250B-MLX-4bit"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

MLX LM

How to use TensorFold/Solar-Open2-250B-MLX-4bit with MLX LM:

Generate or start a chat session

# Install MLX LM
uv tool install mlx-lm
# Interactive chat REPL
mlx_lm.chat --model "TensorFold/Solar-Open2-250B-MLX-4bit"

Run an OpenAI-compatible server

# Install MLX LM
uv tool install mlx-lm
# Start the server
mlx_lm.server --model "TensorFold/Solar-Open2-250B-MLX-4bit"
# Calling the OpenAI-compatible server with curl
curl -X POST "http://localhost:8000/v1/chat/completions" \
   -H "Content-Type: application/json" \
   --data '{
     "model": "TensorFold/Solar-Open2-250B-MLX-4bit",
     "messages": [
       {"role": "user", "content": "Hello"}
     ]
   }'

Hermes Agent

How to use TensorFold/Solar-Open2-250B-MLX-4bit 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 "TensorFold/Solar-Open2-250B-MLX-4bit"

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 TensorFold/Solar-Open2-250B-MLX-4bit

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use TensorFold/Solar-Open2-250B-MLX-4bit with OpenClaw:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "TensorFold/Solar-Open2-250B-MLX-4bit"

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 "TensorFold/Solar-Open2-250B-MLX-4bit" \
  --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"

ashxhart commited on 9 days ago

Commit

d34aa99

verified ·

1 Parent(s): f321918

Rebrand model card to TensorFold

Browse files

Files changed (1) hide show

README.md +13 -8

README.md CHANGED Viewed

@@ -19,6 +19,11 @@ tags:
   - 4bit
 ---
 # Solar-Open2-250B-MLX-4bit
@@ -45,7 +50,7 @@ Solar Open2 is not yet a stock `mlx-lm` architecture in many installs. This repo
 ```bash
 mlx_lm.server \
-  --model Vontra/Solar-Open2-250B-MLX-4bit \
   --host 0.0.0.0 \
   --port 8021 \
   --trust-remote-code \
@@ -76,7 +81,7 @@ pip install -U mlx-lm
 from mlx_lm import load, generate
-model, tokenizer = load("Vontra/Solar-Open2-250B-MLX-4bit")
 prompt = "Write a short Python function that validates an IPv4 CIDR string."
 print(generate(model, tokenizer, prompt=prompt, max_tokens=256, verbose=True))
 ```
@@ -85,7 +90,7 @@ print(generate(model, tokenizer, prompt=prompt, max_tokens=256, verbose=True))
 ## Notes
-This is an independent community conversion under the Vontra organization. It is not an official Upstage release.
 ## License
@@ -95,10 +100,10 @@ The source model is released under the Upstage Solar License. A copy is included
-<!-- vontra-chooser-start -->
 ## Choose for your Mac
-[64GB Macs](https://huggingface.co/collections/Vontra/mlx-models-for-64gb-macs-6a9fefda17932216ec9ab457) · [128GB Macs](https://huggingface.co/collections/Vontra/mlx-models-for-128gb-macs-6a9ff0abd31bc9abbe7922d7) · [256GB Macs](https://huggingface.co/collections/Vontra/mlx-models-for-256gb-macs-6a9ff0ef9fed7c5bdca15e9b)
 No measured memory tier is assigned here. The collections use published M3 Studio peaks with at least 25% nominal headroom; fit on other Macs is an estimate, and full context is not guaranteed. Start with short context and one request.
@@ -109,7 +114,7 @@ The exact tested oMLX application version is not recorded here; a library versio
 ### Quick start and demo prompt
 ```bash
-hf download Vontra/Solar-Open2-250B-MLX-4bit --local-dir ./models/Solar-Open2-250B-MLX-4bit
 ```
 Add the downloaded folder to oMLX model directories, refresh the list, and follow this card's architecture and MTP compatibility requirements before loading.
@@ -122,5 +127,5 @@ Explain why the sky looks blue in three short sentences.
 This is a demo prompt to try, not a recorded successful run; a captured demonstration for this documentation update is not yet available.
-[Follow Vontra for new Apple Silicon releases and fixes.](https://huggingface.co/Vontra)
-<!-- vontra-chooser-end -->

   - 4bit
 ---
+<p align="center">
+  <a href="https://tensorfold.dev">
+    <img src="https://huggingface.co/spaces/TensorFold/README/resolve/main/tensorfold-logo.png" alt="TensorFold" width="160">
+  </a>
+</p>
 # Solar-Open2-250B-MLX-4bit
 ```bash
 mlx_lm.server \
+  --model TensorFold/Solar-Open2-250B-MLX-4bit \
   --host 0.0.0.0 \
   --port 8021 \
   --trust-remote-code \
 from mlx_lm import load, generate
+model, tokenizer = load("TensorFold/Solar-Open2-250B-MLX-4bit")
 prompt = "Write a short Python function that validates an IPv4 CIDR string."
 print(generate(model, tokenizer, prompt=prompt, max_tokens=256, verbose=True))
 ```
 ## Notes
+This is an independent community conversion under the TensorFold organization. It is not an official Upstage release.
 ## License
+<!-- TensorFold-chooser-start -->
 ## Choose for your Mac
+[64GB Macs](https://huggingface.co/collections/TensorFold/mlx-models-for-64gb-macs-6a9fefda17932216ec9ab457) · [128GB Macs](https://huggingface.co/collections/TensorFold/mlx-models-for-128gb-macs-6a9ff0abd31bc9abbe7922d7) · [256GB Macs](https://huggingface.co/collections/TensorFold/mlx-models-for-256gb-macs-6a9ff0ef9fed7c5bdca15e9b)
 No measured memory tier is assigned here. The collections use published M3 Studio peaks with at least 25% nominal headroom; fit on other Macs is an estimate, and full context is not guaranteed. Start with short context and one request.
 ### Quick start and demo prompt
 ```bash
+hf download TensorFold/Solar-Open2-250B-MLX-4bit --local-dir ./models/Solar-Open2-250B-MLX-4bit
 ```
 Add the downloaded folder to oMLX model directories, refresh the list, and follow this card's architecture and MTP compatibility requirements before loading.
 This is a demo prompt to try, not a recorded successful run; a captured demonstration for this documentation update is not yet available.
+[Follow TensorFold for new Apple Silicon releases and fixes.](https://huggingface.co/TensorFold)
+<!-- TensorFold-chooser-end -->