Instructions to use LetheanNetwork/lemer-bk with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use LetheanNetwork/lemer-bk with Transformers:

# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("LetheanNetwork/lemer-bk")
model = AutoModelForMultimodalLM.from_pretrained("LetheanNetwork/lemer-bk", device_map="auto")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
inputs = processor.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use LetheanNetwork/lemer-bk with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf LetheanNetwork/lemer-bk:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf LetheanNetwork/lemer-bk:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf LetheanNetwork/lemer-bk:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf LetheanNetwork/lemer-bk:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf LetheanNetwork/lemer-bk:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf LetheanNetwork/lemer-bk:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf LetheanNetwork/lemer-bk:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf LetheanNetwork/lemer-bk:Q4_K_M

Use Docker

docker model run hf.co/LetheanNetwork/lemer-bk:Q4_K_M

LM Studio
Jan
Ollama
How to use LetheanNetwork/lemer-bk with Ollama:
```
ollama run hf.co/LetheanNetwork/lemer-bk:Q4_K_M
```

Unsloth Studio

How to use LetheanNetwork/lemer-bk with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for LetheanNetwork/lemer-bk to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for LetheanNetwork/lemer-bk to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for LetheanNetwork/lemer-bk to start chatting

How to use LetheanNetwork/lemer-bk with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf LetheanNetwork/lemer-bk:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "LetheanNetwork/lemer-bk:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use LetheanNetwork/lemer-bk with Docker Model Runner:
```
docker model run hf.co/LetheanNetwork/lemer-bk:Q4_K_M
```

Lemonade

How to use LetheanNetwork/lemer-bk with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull LetheanNetwork/lemer-bk:Q4_K_M

Run and chat with the model

lemonade run user.lemer-bk-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use LetheanNetwork/lemer-bk with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf LetheanNetwork/lemer-bk:Q4_K_M

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 LetheanNetwork/lemer-bk:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use LetheanNetwork/lemer-bk with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf LetheanNetwork/lemer-bk:Q4_K_M

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 "LetheanNetwork/lemer-bk:Q4_K_M" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

Snider Virgil commited on Apr 6

Commit

c218b73

1 Parent(s): 95412c4

fix: config.json matches HF 4-bit safetensors (BitsAndBytes NF4)

Browse files

Files changed (1) hide show

config.json +19 -8

config.json CHANGED Viewed

@@ -56,6 +56,21 @@
   "image_token_id": 258880,
   "initializer_range": 0.02,
   "model_type": "gemma4",
   "text_config": {
     "attention_bias": false,
     "attention_dropout": 0.0,
@@ -112,6 +127,7 @@
     ],
     "max_position_embeddings": 131072,
     "model_type": "gemma4_text",
     "num_attention_heads": 8,
     "num_experts": null,
     "num_global_key_value_heads": null,
@@ -141,7 +157,7 @@
     "vocab_size_per_layer_input": 262144
   },
   "tie_word_embeddings": true,
-  "transformers_version": "5.5.0.dev0",
   "video_token_id": 258884,
   "vision_config": {
     "_name_or_path": "",
@@ -186,10 +202,5 @@
     "standardize": false,
     "use_clipped_linears": true
   },
-  "vision_soft_tokens_per_image": 280,
-  "quantization": {
-    "group_size": 64,
-    "bits": 4,
-    "mode": "affine"
-  }
-}

   "image_token_id": 258880,
   "initializer_range": 0.02,
   "model_type": "gemma4",
+  "quantization_config": {
+    "_load_in_4bit": true,
+    "_load_in_8bit": false,
+    "bnb_4bit_compute_dtype": "bfloat16",
+    "bnb_4bit_quant_storage": "uint8",
+    "bnb_4bit_quant_type": "nf4",
+    "bnb_4bit_use_double_quant": true,
+    "llm_int8_enable_fp32_cpu_offload": false,
+    "llm_int8_has_fp16_weight": false,
+    "llm_int8_skip_modules": null,
+    "llm_int8_threshold": 6.0,
+    "load_in_4bit": true,
+    "load_in_8bit": false,
+    "quant_method": "bitsandbytes"
+  },
   "text_config": {
     "attention_bias": false,
     "attention_dropout": 0.0,
     ],
     "max_position_embeddings": 131072,
     "model_type": "gemma4_text",
+    "moe_intermediate_size": null,
     "num_attention_heads": 8,
     "num_experts": null,
     "num_global_key_value_heads": null,
     "vocab_size_per_layer_input": 262144
   },
   "tie_word_embeddings": true,
+  "transformers_version": "5.5.0",
   "video_token_id": 258884,
   "vision_config": {
     "_name_or_path": "",
     "standardize": false,
     "use_clipped_linears": true
   },
+  "vision_soft_tokens_per_image": 280
+}