Instructions to use afrideva/tinycodellama-1.3b-5k-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use afrideva/tinycodellama-1.3b-5k-GGUF 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 afrideva/tinycodellama-1.3b-5k-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf afrideva/tinycodellama-1.3b-5k-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf afrideva/tinycodellama-1.3b-5k-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf afrideva/tinycodellama-1.3b-5k-GGUF: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 afrideva/tinycodellama-1.3b-5k-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf afrideva/tinycodellama-1.3b-5k-GGUF: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 afrideva/tinycodellama-1.3b-5k-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf afrideva/tinycodellama-1.3b-5k-GGUF:Q4_K_M

Use Docker

docker model run hf.co/afrideva/tinycodellama-1.3b-5k-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use afrideva/tinycodellama-1.3b-5k-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "afrideva/tinycodellama-1.3b-5k-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "afrideva/tinycodellama-1.3b-5k-GGUF",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/afrideva/tinycodellama-1.3b-5k-GGUF:Q4_K_M

Ollama
How to use afrideva/tinycodellama-1.3b-5k-GGUF with Ollama:
```
ollama run hf.co/afrideva/tinycodellama-1.3b-5k-GGUF:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use afrideva/tinycodellama-1.3b-5k-GGUF with Docker Model Runner:
```
docker model run hf.co/afrideva/tinycodellama-1.3b-5k-GGUF:Q4_K_M
```

Lemonade

How to use afrideva/tinycodellama-1.3b-5k-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull afrideva/tinycodellama-1.3b-5k-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.tinycodellama-1.3b-5k-GGUF-Q4_K_M

List all available models

lemonade list

Atomic Chat

afrideva commited on Dec 28, 2023

Commit

8b4f293

1 Parent(s): 17d1966

Upload README.md with huggingface_hub

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README.md +36 -0

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	@@ -0,0 +1,36 @@

+---
+base_model: obrmmk/tinycodellama-1.3b-5k
+inference: false
+model_creator: obrmmk
+model_name: tinycodellama-1.3b-5k
+pipeline_tag: text-generation
+quantized_by: afrideva
+tags:
+- gguf
+- ggml
+- quantized
+- q2_k
+- q3_k_m
+- q4_k_m
+- q5_k_m
+- q6_k
+- q8_0
+---
+# obrmmk/tinycodellama-1.3b-5k-GGUF
+Quantized GGUF model files for [tinycodellama-1.3b-5k](https://huggingface.co/obrmmk/tinycodellama-1.3b-5k) from [obrmmk](https://huggingface.co/obrmmk)
+| Name | Quant method | Size |
+| ---- | ---- | ---- |
+| [tinycodellama-1.3b-5k.fp16.gguf](https://huggingface.co/afrideva/tinycodellama-1.3b-5k-GGUF/resolve/main/tinycodellama-1.3b-5k.fp16.gguf) | fp16 | 2.58 GB  |
+| [tinycodellama-1.3b-5k.q2_k.gguf](https://huggingface.co/afrideva/tinycodellama-1.3b-5k-GGUF/resolve/main/tinycodellama-1.3b-5k.q2_k.gguf) | q2_k | 565.81 MB  |
+| [tinycodellama-1.3b-5k.q3_k_m.gguf](https://huggingface.co/afrideva/tinycodellama-1.3b-5k-GGUF/resolve/main/tinycodellama-1.3b-5k.q3_k_m.gguf) | q3_k_m | 644.08 MB  |
+| [tinycodellama-1.3b-5k.q4_k_m.gguf](https://huggingface.co/afrideva/tinycodellama-1.3b-5k-GGUF/resolve/main/tinycodellama-1.3b-5k.q4_k_m.gguf) | q4_k_m | 792.15 MB  |
+| [tinycodellama-1.3b-5k.q5_k_m.gguf](https://huggingface.co/afrideva/tinycodellama-1.3b-5k-GGUF/resolve/main/tinycodellama-1.3b-5k.q5_k_m.gguf) | q5_k_m | 921.00 MB  |
+| [tinycodellama-1.3b-5k.q6_k.gguf](https://huggingface.co/afrideva/tinycodellama-1.3b-5k-GGUF/resolve/main/tinycodellama-1.3b-5k.q6_k.gguf) | q6_k | 1.06 GB  |
+| [tinycodellama-1.3b-5k.q8_0.gguf](https://huggingface.co/afrideva/tinycodellama-1.3b-5k-GGUF/resolve/main/tinycodellama-1.3b-5k.q8_0.gguf) | q8_0 | 1.37 GB  |
+## Original Model Card: