Instructions to use XcaliburMoon/XcaliburBiz-1.8B-report with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries
PEFT
How to use XcaliburMoon/XcaliburBiz-1.8B-report with PEFT:
```
Task type is invalid.
```
Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use XcaliburMoon/XcaliburBiz-1.8B-report 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 XcaliburMoon/XcaliburBiz-1.8B-report:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf XcaliburMoon/XcaliburBiz-1.8B-report:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf XcaliburMoon/XcaliburBiz-1.8B-report:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf XcaliburMoon/XcaliburBiz-1.8B-report: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 XcaliburMoon/XcaliburBiz-1.8B-report:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf XcaliburMoon/XcaliburBiz-1.8B-report: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 XcaliburMoon/XcaliburBiz-1.8B-report:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf XcaliburMoon/XcaliburBiz-1.8B-report:Q4_K_M

Use Docker

docker model run hf.co/XcaliburMoon/XcaliburBiz-1.8B-report:Q4_K_M

LM Studio
Jan

vLLM

How to use XcaliburMoon/XcaliburBiz-1.8B-report with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "XcaliburMoon/XcaliburBiz-1.8B-report"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "XcaliburMoon/XcaliburBiz-1.8B-report",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/XcaliburMoon/XcaliburBiz-1.8B-report:Q4_K_M

Ollama
How to use XcaliburMoon/XcaliburBiz-1.8B-report with Ollama:
```
ollama run hf.co/XcaliburMoon/XcaliburBiz-1.8B-report:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use XcaliburMoon/XcaliburBiz-1.8B-report with Docker Model Runner:
```
docker model run hf.co/XcaliburMoon/XcaliburBiz-1.8B-report:Q4_K_M
```

Lemonade

How to use XcaliburMoon/XcaliburBiz-1.8B-report with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull XcaliburMoon/XcaliburBiz-1.8B-report:Q4_K_M

Run and chat with the model

lemonade run user.XcaliburBiz-1.8B-report-Q4_K_M

List all available models

lemonade list

Atomic Chat

XcaliburMoon commited on 5 days ago

Commit

aac318c

verified ·

1 Parent(s): 68d85db

upload

Browse files

Files changed (1) hide show

sft_record.json +8 -8

sft_record.json CHANGED Viewed

@@ -2,8 +2,8 @@
   "stage": "sft",
   "base": "Qwen/Qwen1.5-1.8B-Chat",
   "init_adapter": "",
-  "examples": 673,
-  "valid_examples": 62,
   "epochs": 3.0,
   "max_seq_len": 2048,
   "lora": {
@@ -11,13 +11,13 @@
     "alpha": 32,
     "dropout": 0.05
   },
-  "train_loss": 1.8141,
   "metrics": {
-    "train_runtime": 278.7263,
-    "train_samples_per_second": 7.244,
-    "train_steps_per_second": 0.463,
-    "total_flos": 2.808977346378547e+16,
-    "train_loss": 1.814143927522408,
     "epoch": 3.0
   },
   "adapter": "/workspace/xcaliburbiz/out/sft/adapter"

   "stage": "sft",
   "base": "Qwen/Qwen1.5-1.8B-Chat",
   "init_adapter": "",
+  "examples": 658,
+  "valid_examples": 69,
   "epochs": 3.0,
   "max_seq_len": 2048,
   "lora": {
     "alpha": 32,
     "dropout": 0.05
   },
+  "train_loss": 1.7065,
   "metrics": {
+    "train_runtime": 289.9988,
+    "train_samples_per_second": 6.807,
+    "train_steps_per_second": 0.434,
+    "total_flos": 2.8481243474804736e+16,
+    "train_loss": 1.70650429385049,
     "epoch": 3.0
   },
   "adapter": "/workspace/xcaliburbiz/out/sft/adapter"