Instructions to use ia-espirita/riv-ai with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use ia-espirita/riv-ai 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 ia-espirita/riv-ai:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf ia-espirita/riv-ai:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf ia-espirita/riv-ai:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf ia-espirita/riv-ai: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 ia-espirita/riv-ai:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf ia-espirita/riv-ai: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 ia-espirita/riv-ai:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf ia-espirita/riv-ai:Q4_K_M

Use Docker

docker model run hf.co/ia-espirita/riv-ai:Q4_K_M

LM Studio
Jan

vLLM

How to use ia-espirita/riv-ai with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ia-espirita/riv-ai"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ia-espirita/riv-ai",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/ia-espirita/riv-ai:Q4_K_M

Ollama
How to use ia-espirita/riv-ai with Ollama:
```
ollama run hf.co/ia-espirita/riv-ai:Q4_K_M
```
Unsloth Desktop

How to use ia-espirita/riv-ai with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf ia-espirita/riv-ai:Q4_K_M

Configure the model in Pi

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

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use ia-espirita/riv-ai with Docker Model Runner:
```
docker model run hf.co/ia-espirita/riv-ai:Q4_K_M
```

Lemonade

How to use ia-espirita/riv-ai with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull ia-espirita/riv-ai:Q4_K_M

Run and chat with the model

lemonade run user.riv-ai-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use ia-espirita/riv-ai with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf ia-espirita/riv-ai: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 ia-espirita/riv-ai:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use ia-espirita/riv-ai with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf ia-espirita/riv-ai: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 "ia-espirita/riv-ai: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"

ia-espirita commited on Mar 15

Commit

0454832

verified ·

1 Parent(s): d99ffb3

Upload model trained with Unsloth

Browse files

Upload model trained with Unsloth 2x faster

Files changed (3) hide show

README.md +18 -17
adapter_config.json +50 -0
adapter_model.safetensors +3 -0

README.md CHANGED Viewed

@@ -1,28 +1,29 @@
 ---
 language:
-  - pt
 license: apache-2.0
 tags:
-  - spiritism
-  - kardec
-  - espiritismo
-  - allan-kardec
-  - religion
-  - portuguese
-  - brazilian
-  - fine-tuned
-  - qlora
-  - llama-3
-  - spirituality
-  - riv-ai
-  - espírita
 datasets:
-  - ia-espirita/riv-ai-dataset
 base_model: meta-llama/Meta-Llama-3-8B-Instruct
 pipeline_tag: text-generation
 model-index:
-  - name: riv-ai
-    results: []
 ---
 # 🔮 RIV AI — Modelo de IA Espírita Open Source

 ---
 language:
+- pt
 license: apache-2.0
 tags:
+- spiritism
+- kardec
+- espiritismo
+- allan-kardec
+- religion
+- portuguese
+- brazilian
+- fine-tuned
+- qlora
+- llama-3
+- spirituality
+- riv-ai
+- espírita
+- unsloth
 datasets:
+- ia-espirita/riv-ai-dataset
 base_model: meta-llama/Meta-Llama-3-8B-Instruct
 pipeline_tag: text-generation
 model-index:
+- name: riv-ai
+  results: []
 ---
 # 🔮 RIV AI — Modelo de IA Espírita Open Source

adapter_config.json ADDED Viewed

	@@ -0,0 +1,50 @@

+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": {
+    "base_model_class": "LlamaForCausalLM",
+    "parent_library": "transformers.models.llama.modeling_llama",
+    "unsloth_fixed": true
+  },
+  "base_model_name_or_path": "unsloth/meta-llama-3.1-8b-instruct-unsloth-bnb-4bit",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_bias": false,
+  "lora_dropout": 0,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.18.1",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "o_proj",
+    "up_proj",
+    "q_proj",
+    "down_proj",
+    "v_proj",
+    "gate_proj",
+    "k_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

adapter_model.safetensors ADDED Viewed

	@@ -0,0 +1,3 @@

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