Instructions to use fedric95/gemma-2-2b-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use fedric95/gemma-2-2b-GGUF with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="fedric95/gemma-2-2b-GGUF")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("fedric95/gemma-2-2b-GGUF", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use fedric95/gemma-2-2b-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 fedric95/gemma-2-2b-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf fedric95/gemma-2-2b-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 fedric95/gemma-2-2b-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf fedric95/gemma-2-2b-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 fedric95/gemma-2-2b-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf fedric95/gemma-2-2b-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 fedric95/gemma-2-2b-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf fedric95/gemma-2-2b-GGUF:Q4_K_M

Use Docker

docker model run hf.co/fedric95/gemma-2-2b-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use fedric95/gemma-2-2b-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "fedric95/gemma-2-2b-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "fedric95/gemma-2-2b-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/fedric95/gemma-2-2b-GGUF:Q4_K_M

SGLang

How to use fedric95/gemma-2-2b-GGUF with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "fedric95/gemma-2-2b-GGUF" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "fedric95/gemma-2-2b-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "fedric95/gemma-2-2b-GGUF" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "fedric95/gemma-2-2b-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Ollama
How to use fedric95/gemma-2-2b-GGUF with Ollama:
```
ollama run hf.co/fedric95/gemma-2-2b-GGUF:Q4_K_M
```

Unsloth Studio

How to use fedric95/gemma-2-2b-GGUF 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 fedric95/gemma-2-2b-GGUF 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 fedric95/gemma-2-2b-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for fedric95/gemma-2-2b-GGUF to start chatting

Docker Model Runner
How to use fedric95/gemma-2-2b-GGUF with Docker Model Runner:
```
docker model run hf.co/fedric95/gemma-2-2b-GGUF:Q4_K_M
```

Lemonade

How to use fedric95/gemma-2-2b-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull fedric95/gemma-2-2b-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.gemma-2-2b-GGUF-Q4_K_M

List all available models

lemonade list

Atomic Chat

fedric95 commited on Aug 31, 2024

Commit

3f3059b

verified ·

1 Parent(s): 82d5847

Upload ./gemma-2-2b-Q3_K_S.mmlu.txt with huggingface_hub

Browse files

Files changed (1) hide show

gemma-2-2b-Q3_K_S.mmlu.txt +1558 -0

gemma-2-2b-Q3_K_S.mmlu.txt ADDED Viewed

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+1309	32.00916730
+1310	32.06106870
+1311	32.11289092
+1312	32.16463415
+1313	32.21629855
+1314	32.19178082
+1315	32.24334601
+1316	32.21884498
+1317	32.27031131
+1318	32.24582701
+1319	32.29719484
+1320	32.27272727
+1321	32.24829674
+1322	32.22390318
+1323	32.19954649
+1324	32.17522659
+1325	32.22641509
+1326	32.20211161
+1327	32.25320271
+1328	32.30421687
+1329	32.27990971
+1330	32.25563910
+1331	32.23140496
+1332	32.28228228
+1333	32.33308327
+1334	32.38380810
+1335	32.43445693
+1336	32.48502994
+1337	32.53552730
+1338	32.51121076
+1339	32.56161314
+1340	32.61194030
+1341	32.58762118
+1342	32.56333830
+1343	32.53909159
+1344	32.51488095
+1345	32.56505576
+1346	32.61515602
+1347	32.66518189
+1348	32.64094955
+1349	32.61675315
+1350	32.59259259
+1351	32.56846780
+1352	32.54437870
+1353	32.52032520
+1354	32.49630724
+1355	32.54612546
+1356	32.59587021
+1357	32.64554164
+1358	32.69513991
+1359	32.74466519
+1360	32.79411765
+1361	32.77002204
+1362	32.74596182
+1363	32.72193690
+1364	32.77126100
+1365	32.74725275
+1366	32.79648609
+1367	32.84564740
+1368	32.82163743
+1369	32.87070855
+1370	32.84671533
+1371	32.82275711
+1372	32.79883382
+1373	32.77494538
+1374	32.75109170
+1375	32.80000000
+1376	32.84883721
+1377	32.89760349
+1378	32.94629898
+1379	32.99492386
+1380	32.97101449
+1381	32.94713975
+1382	32.92329957
+1383	32.97180043
+1384	32.94797688
+1385	32.92418773
+1386	32.97258297
+1387	33.02090844
+1388	32.99711816
+1389	33.04535637
+1390	33.09352518
+1391	33.14162473
+1392	33.11781609
+1393	33.09404164
+1394	33.14203730
+1395	33.18996416
+1396	33.16618911
+1397	33.21403006
+1398	33.26180258
+1399	33.30950679
+1400	33.35714286
+1401	33.33333333
+1402	33.30955777
+1403	33.28581611
+1404	33.26210826
+1405	33.23843416
+1406	33.21479374
+1407	33.26226013
+1408	33.30965909
+1409	33.28601845
+1410	33.33333333
+1411	33.30970943
+1412	33.28611898
+1413	33.26256192
+1414	33.23903819
+1415	33.28621908
+1416	33.33333333
+1417	33.30980946
+1418	33.35684062
+1419	33.33333333
+1420	33.30985915
+1421	33.28641802
+1422	33.26300985
+1423	33.23963457
+1424	33.21629213
+1425	33.19298246
+1426	33.23983170
+1427	33.21653819
+1428	33.19327731
+1429	33.17004899
+1430	33.14685315
+1431	33.12368973
+1432	33.17039106
+1433	33.14724355
+1434	33.12412831
+1435	33.10104530
+1436	33.07799443
+1437	33.05497564
+1438	33.10152990
+1439	33.14801946
+1440	33.19444444
+1441	33.17140874
+1442	33.21775312
+1443	33.19473319
+1444	33.24099723
+1445	33.28719723
+1446	33.26417704
+1447	33.31029717
+1448	33.35635359
+1449	33.40234645
+1450	33.37931034
+1451	33.35630600
+1452	33.40220386
+1453	33.37921542
+1454	33.35625860
+1455	33.40206186
+1456	33.44780220
+1457	33.42484557
+1458	33.40192044
+1459	33.44756683
+1460	33.49315068
+1461	33.53867214
+1462	33.51573187
+1463	33.49282297
+1464	33.46994536
+1465	33.44709898
+1466	33.42428377
+1467	33.46966599
+1468	33.44686649
+1469	33.49217155
+1470	33.46938776
+1471	33.44663494
+1472	33.42391304
+1473	33.40122200
+1474	33.44640434
+1475	33.42372881
+1476	33.46883469
+1477	33.44617468
+1478	33.49120433
+1479	33.46855984
+1480	33.44594595
+1481	33.49088454
+1482	33.53576248
+1483	33.51314902
+1484	33.49056604
+1485	33.53535354
+1486	33.58008075
+1487	33.62474781
+1488	33.60215054
+1489	33.57958361
+1490	33.62416107
+1491	33.66867874
+1492	33.71313673
+1493	33.69055593
+1494	33.73493976
+1495	33.71237458
+1496	33.68983957
+1497	33.73413494
+1498	33.77837116
+1499	33.75583722
+1500	33.80000000
+1501	33.77748168
+1502	33.75499334
+1503	33.79906853
+1504	33.84308511
+1505	33.82059801
+1506	33.86454183
+1507	33.84207034
+1508	33.81962865
+1509	33.79721670
+1510	33.84105960
+1511	33.81866314
+1512	33.79629630
+1513	33.77395902
+1514	33.75165125
+1515	33.79537954
+1516	33.77308707
+1517	33.75082399
+1518	33.72859025
+1519	33.77221856
+1520	33.75000000
+1521	33.72781065
+1522	33.77135348
+1523	33.74917925
+1524	33.79265092
+1525	33.77049180
+1526	33.81389253
+1527	33.85723641
+1528	33.83507853
+1529	33.81294964
+1530	33.79084967
+1531	33.76877858
+1532	33.81201044
+1533	33.78995434
+1534	33.76792699
+1535	33.74592834
+1536	33.72395833
+1537	33.76707872
+1538	33.81014304
+1539	33.85315140
+1540	33.89610390
+1541	33.93900065
+1542	33.98184176
+1543	33.95981854
+1544	33.93782383
+1545	33.91585761
+1546	33.95860285
+1547	33.93665158
+1548	33.91472868
+ Final result: 33.9147 +/- 1.2037
+Random chance: 25.0000 +/- 1.1009