Instructions to use eaddario/Dolphin3.0-Mistral-24B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use eaddario/Dolphin3.0-Mistral-24B-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="eaddario/Dolphin3.0-Mistral-24B-GGUF",
	filename="Dolphin3.0-Mistral-24B-F16.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use eaddario/Dolphin3.0-Mistral-24B-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 eaddario/Dolphin3.0-Mistral-24B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf eaddario/Dolphin3.0-Mistral-24B-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 eaddario/Dolphin3.0-Mistral-24B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf eaddario/Dolphin3.0-Mistral-24B-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 eaddario/Dolphin3.0-Mistral-24B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf eaddario/Dolphin3.0-Mistral-24B-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 eaddario/Dolphin3.0-Mistral-24B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf eaddario/Dolphin3.0-Mistral-24B-GGUF:Q4_K_M

Use Docker

docker model run hf.co/eaddario/Dolphin3.0-Mistral-24B-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use eaddario/Dolphin3.0-Mistral-24B-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "eaddario/Dolphin3.0-Mistral-24B-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": "eaddario/Dolphin3.0-Mistral-24B-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/eaddario/Dolphin3.0-Mistral-24B-GGUF:Q4_K_M

Ollama
How to use eaddario/Dolphin3.0-Mistral-24B-GGUF with Ollama:
```
ollama run hf.co/eaddario/Dolphin3.0-Mistral-24B-GGUF:Q4_K_M
```

Unsloth Studio

How to use eaddario/Dolphin3.0-Mistral-24B-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 eaddario/Dolphin3.0-Mistral-24B-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 eaddario/Dolphin3.0-Mistral-24B-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for eaddario/Dolphin3.0-Mistral-24B-GGUF to start chatting

Atomic Chat new
Docker Model Runner
How to use eaddario/Dolphin3.0-Mistral-24B-GGUF with Docker Model Runner:
```
docker model run hf.co/eaddario/Dolphin3.0-Mistral-24B-GGUF:Q4_K_M
```

Lemonade

How to use eaddario/Dolphin3.0-Mistral-24B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull eaddario/Dolphin3.0-Mistral-24B-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Dolphin3.0-Mistral-24B-GGUF-Q4_K_M

List all available models

lemonade list

Dolphin3.0-Mistral-24B-GGUF

File size: 31,362 Bytes

common_init_from_params: setting dry_penalty_last_n to ctx_size = 768
common_init_from_params: warming up the model with an empty run - please wait ... (--no-warmup to disable)

system_info: n_threads = 8 (n_threads_batch = 8) / 16 | CUDA : ARCHS = 750 | USE_GRAPHS = 1 | PEER_MAX_BATCH_SIZE = 128 | CPU : SSE3 = 1 | SSSE3 = 1 | AVX = 1 | AVX2 = 1 | F16C = 1 | FMA = 1 | AVX512 = 1 | AVX512_VNNI = 1 | LLAMAFILE = 1 | OPENMP = 1 | AARCH64_REPACK = 1 |
winogrande_score : loaded 1267 tasks from prompt.
winogrande_score : selecting 750 random tasks
winogrande_score : tokenizing selected tasks
winogrande_score : calculating winogrande score over selected tasks.
1	100.0000	 -3.030289   -4.267672  1  1
2	100.0000	 -2.381885   -2.869143  1  1
3	100.0000	 -2.923971   -2.657783  2  2
4	75.0000	 -5.864796   -5.334209  2  1
5	60.0000	 -1.690567   -2.169047  1  2
6	66.6667	 -4.346579   -4.867627  1  1
7	71.4286	 -5.389299   -3.567749  2  2
8	75.0000	 -2.735904   -1.728666  2  2
9	77.7778	 -3.851863   -6.865726  1  1
10	80.0000	 -1.910518   -1.474996  2  2
11	81.8182	-11.432777   -5.613386  2  2
12	83.3333	 -5.081769   -2.254091  2  2
13	84.6154	 -2.392946   -4.168796  1  1
14	85.7143	 -2.829790   -4.088213  1  1
15	80.0000	 -5.748989   -6.646214  1  2
16	81.2500	 -3.318846   -2.403951  2  2
17	76.4706	 -7.685862   -7.785131  1  2
18	77.7778	 -1.378434   -3.334933  1  1
19	78.9474	 -3.344927   -5.751595  1  1
20	80.0000	 -2.232492   -3.272261  1  1
21	80.9524	 -2.832374   -3.589564  1  1
22	81.8182	 -2.957155   -2.730617  2  2
23	82.6087	 -4.620653   -5.225407  1  1
24	83.3333	 -1.786745   -2.142635  1  1
25	84.0000	 -2.143852   -1.947989  2  2
26	84.6154	 -3.084358   -5.718203  1  1
27	85.1852	 -6.078652   -5.777953  2  2
28	85.7143	 -4.108110   -4.783604  1  1
29	86.2069	 -4.349818   -4.644498  1  1
30	86.6667	 -2.818999   -2.574831  2  2
31	87.0968	 -4.767624   -5.504377  1  1
32	87.5000	 -5.016343   -6.674181  1  1
33	87.8788	 -4.389029   -7.066305  1  1
34	88.2353	 -2.860559   -3.651458  1  1
35	85.7143	 -4.301114   -4.387789  1  2
36	83.3333	 -3.909918   -4.340178  1  2
37	83.7838	 -3.380316   -3.726447  1  1
38	84.2105	 -2.839258   -2.912989  1  1
39	84.6154	 -4.074422   -3.736579  2  2
40	82.5000	 -3.198246   -4.768963  1  2
41	82.9268	 -1.508941   -3.296902  1  1
42	83.3333	 -1.359600   -2.366889  1  1
43	83.7209	 -3.051458   -2.920488  2  2
44	84.0909	 -2.235665   -1.321746  2  2
45	84.4444	 -0.024408  -13.420095  1  1
46	84.7826	 -2.835540   -2.846826  1  1
47	82.9787	 -2.920839   -3.432441  1  2
48	83.3333	 -4.518325   -4.298708  2  2
49	83.6735	 -1.786874   -2.057884  1  1
50	84.0000	 -3.872544   -3.493695  2  2
51	84.3137	 -1.872713   -2.146280  1  1
52	84.6154	 -3.107421   -2.985106  2  2
53	84.9057	 -3.305336   -3.992992  1  1
54	85.1852	 -1.773478   -0.977834  2  2
55	85.4545	 -2.477736   -2.179825  2  2
56	83.9286	 -4.205441   -4.311349  1  2
57	84.2105	 -3.301210   -2.127848  2  2
58	84.4828	 -2.233706   -4.184767  1  1
59	84.7458	 -3.668360   -3.354497  2  2
60	85.0000	 -3.613734   -2.721025  2  2
61	83.6066	 -3.895145   -3.745065  2  1
62	83.8710	 -6.203897   -6.430196  1  1
63	84.1270	 -4.812179   -4.734004  2  2
64	84.3750	 -4.158387   -4.349191  1  1
65	84.6154	 -3.936884   -2.826343  2  2
66	84.8485	 -2.741928   -2.976620  1  1
67	85.0746	 -2.465173   -1.785962  2  2
68	83.8235	 -6.183480   -7.200541  1  2
69	84.0580	 -4.620569   -7.845737  1  1
70	84.2857	 -2.912156   -2.640945  2  2
71	83.0986	 -3.187897   -2.770475  2  1
72	81.9444	 -3.691250   -3.893784  1  2
73	80.8219	 -2.977329   -2.965618  2  1
74	81.0811	 -2.343515   -2.632432  1  1
75	81.3333	 -1.527201   -3.041751  1  1
76	81.5789	 -1.441287   -4.435414  1  1
77	81.8182	 -2.925711   -2.111023  2  2
78	82.0513	 -0.845920   -1.847918  1  1
79	81.0127	 -2.456840   -2.673859  1  2
80	81.2500	 -2.376108   -4.128597  1  1
81	81.4815	 -4.770855   -3.015057  2  2
82	81.7073	 -3.988331   -3.609268  2  2
83	81.9277	 -5.730814   -5.300461  2  2
84	82.1429	 -2.608254   -2.455806  2  2
85	82.3529	 -3.355926   -3.860609  1  1
86	81.3953	 -5.729423   -5.885466  1  2
87	80.4598	 -1.136913   -0.563640  2  1
88	80.6818	 -4.415485   -4.730796  1  1
89	80.8989	 -3.680503   -4.202570  1  1
90	81.1111	 -5.601779   -3.773275  2  2
91	81.3187	 -3.873737   -4.485710  1  1
92	81.5217	 -5.213562   -4.584626  2  2
93	81.7204	 -2.909552   -1.131114  2  2
94	81.9149	 -4.903496   -3.438439  2  2
95	82.1053	 -4.613325   -5.833312  1  1
96	82.2917	 -1.944308   -2.721990  1  1
97	82.4742	 -4.711425   -4.821055  1  1
98	82.6531	 -4.215739   -3.654695  2  2
99	82.8283	 -2.938283   -3.164899  1  1
100	83.0000	 -8.769339   -6.526994  2  2
101	83.1683	 -5.618390   -5.080384  2  2
102	83.3333	 -2.514974   -4.045968  1  1
103	83.4951	 -2.258080   -1.682639  2  2
104	83.6538	 -7.394264   -6.866418  2  2
105	83.8095	 -0.628146   -1.651997  1  1
106	83.9623	 -2.955274   -2.145141  2  2
107	84.1121	 -3.471576   -2.705228  2  2
108	84.2593	 -5.145457   -3.194171  2  2
109	83.4862	 -4.485496   -4.894126  1  2
110	83.6364	 -4.803097   -4.471797  2  2
111	83.7838	 -2.616278   -2.543988  2  2
112	83.0357	 -4.031371   -3.428721  2  1
113	83.1858	 -5.130284   -4.310742  2  2
114	83.3333	 -4.558233   -5.080987  1  1
115	82.6087	 -3.207627   -2.917451  2  1
116	82.7586	 -2.973275   -2.354186  2  2
117	82.9060	 -4.021898   -3.595287  2  2
118	83.0508	 -1.081766   -2.902860  1  1
119	83.1933	 -2.306876   -3.152713  1  1
120	83.3333	 -2.279723   -2.539940  1  1
121	83.4711	 -1.744565   -0.562707  2  2
122	83.6066	 -7.904608   -6.091308  2  2
123	83.7398	 -3.318674   -3.926871  1  1
124	83.8710	 -3.084959   -2.678823  2  2
125	84.0000	 -2.440856   -2.052066  2  2
126	84.1270	 -6.951051   -6.796216  2  2
127	84.2520	 -2.300787   -1.507988  2  2
128	83.5938	 -1.312316   -1.286480  2  1
129	83.7209	 -2.397241   -1.074499  2  2
130	83.8462	 -6.193514   -3.731537  2  2
131	83.9695	 -3.123223   -3.070530  2  2
132	84.0909	 -1.717843   -0.890796  2  2
133	84.2105	 -1.516537   -5.099413  1  1
134	84.3284	 -5.806606   -4.981279  2  2
135	84.4444	 -3.807867   -4.360890  1  1
136	84.5588	 -5.442430   -3.734385  2  2
137	84.6715	 -5.586627   -5.854872  1  1
138	84.7826	 -5.535043   -4.904249  2  2
139	84.8921	 -3.247361   -4.442173  1  1
140	85.0000	 -1.862091   -0.971529  2  2
141	85.1064	 -4.282479   -3.651798  2  2
142	85.2113	 -3.159697   -1.489942  2  2
143	85.3147	 -2.417799   -5.196903  1  1
144	84.7222	 -2.692152   -2.677456  2  1
145	84.1379	 -1.870323  -17.424105  1  2
146	83.5616	 -3.613775   -3.795692  1  2
147	83.6735	 -4.770811   -4.255833  2  2
148	83.7838	 -1.302837   -2.256811  1  1
149	83.8926	 -5.540620   -3.698289  2  2
150	84.0000	 -4.517198   -3.756181  2  2
151	84.1060	 -2.020453   -2.326734  1  1
152	83.5526	 -3.739096   -4.059584  1  2
153	83.6601	 -3.257429   -3.789754  1  1
154	83.1169	 -4.315406   -3.931814  2  1
155	82.5806	 -1.900197   -2.883623  1  2
156	82.6923	 -2.536721   -2.686933  1  1
157	82.8025	 -2.593250   -4.920130  1  1
158	82.9114	 -4.640135   -3.795552  2  2
159	83.0189	 -2.596928   -5.335842  1  1
160	82.5000	 -3.302296   -3.399432  1  2
161	82.6087	 -1.852211   -3.658433  1  1
162	82.0988	 -1.747812  -16.345299  1  2
163	82.2086	 -1.789694   -1.975808  1  1
164	82.3171	 -6.075574   -4.989811  2  2
165	81.8182	 -4.560736   -4.603802  1  2
166	81.9277	 -3.617351   -3.311821  2  2
167	81.4371	 -3.726254   -3.548749  2  1
168	81.5476	 -6.419784   -5.830340  2  2
169	81.0651	 -3.860372   -4.206285  1  2
170	80.5882	 -3.903354   -3.765528  2  1
171	80.7018	 -4.524688   -5.407024  1  1
172	80.8140	 -3.566670   -4.086275  1  1
173	80.9249	 -3.220229   -2.779962  2  2
174	81.0345	 -6.355672   -6.240392  2  2
175	81.1429	 -2.969284   -3.564597  1  1
176	81.2500	 -1.582421   -2.764597  1  1
177	81.3559	 -7.109993   -5.755658  2  2
178	80.8989	 -2.244970   -2.017991  2  1
179	81.0056	 -2.571097   -3.269831  1  1
180	81.1111	 -6.965685   -4.886577  2  2
181	81.2155	 -3.769822   -2.664910  2  2
182	81.3187	 -3.656527   -3.030478  2  2
183	81.4208	 -6.159286   -5.883609  2  2
184	81.5217	 -1.737151   -2.763427  1  1
185	81.6216	 -4.583277   -4.365178  2  2
186	81.7204	 -1.943842   -2.929309  1  1
187	81.8182	 -4.115646   -4.081410  2  2
188	81.3830	 -3.390838   -3.187313  2  1
189	80.9524	 -4.649057   -4.789278  1  2
190	80.5263	 -5.648766   -5.878254  1  2
191	80.6283	 -2.225132   -3.522481  1  1
192	80.7292	 -4.497695   -2.697257  2  2
193	80.8290	 -3.685055   -3.678717  2  2
194	80.4124	 -1.968908   -2.340758  1  2
195	80.0000	 -4.854474   -3.706882  2  1
196	79.5918	 -3.727946   -3.817662  1  2
197	79.6954	 -0.461897   -5.291561  1  1
198	79.7980	 -3.673247   -7.280559  1  1
199	79.8995	 -5.322187   -4.585287  2  2
200	80.0000	 -3.257841   -2.804220  2  2
201	80.0995	 -2.305571   -2.847395  1  1
202	80.1980	 -8.872674   -8.427680  2  2
203	79.8030	 -2.841636   -2.970183  1  2
204	79.9020	 -1.931318   -3.340894  1  1
205	80.0000	 -2.468925   -1.692367  2  2
206	80.0971	 -5.551071   -5.367128  2  2
207	80.1932	 -3.824381   -3.997232  1  1
208	80.2885	 -4.423236   -3.436256  2  2
209	80.3828	 -4.827329   -2.381071  2  2
210	80.0000	 -7.366334   -7.740288  1  2
211	80.0948	 -4.196527   -4.926610  1  1
212	80.1887	 -4.933229   -3.885992  2  2
213	79.8122	 -4.584283   -6.005397  1  2
214	79.9065	 -2.447254   -2.652066  1  1
215	80.0000	 -5.223330   -4.963465  2  2
216	79.6296	 -3.119525   -2.660846  2  1
217	79.7235	 -0.817130   -0.917353  1  1
218	79.8165	 -2.263842   -2.139149  2  2
219	79.9087	 -3.105193   -3.471590  1  1
220	80.0000	 -3.181651   -2.748635  2  2
221	80.0905	 -3.214250  -10.173682  1  1
222	79.7297	 -0.730463  -13.678673  1  2
223	79.8206	 -4.441327   -3.643904  2  2
224	79.9107	 -7.883078   -5.262507  2  2
225	80.0000	 -3.096609   -2.911411  2  2
226	80.0885	 -2.883400   -4.290939  1  1
227	79.7357	 -4.002244   -3.928179  2  1
228	79.8246	 -1.039500   -1.413438  1  1
229	79.9127	 -3.626859   -3.514011  2  2
230	80.0000	 -2.601394   -3.521525  1  1
231	79.6537	 -2.132514   -2.128114  2  1
232	79.7414	 -2.832458   -0.940620  2  2
233	79.8283	 -1.553856   -2.084794  1  1
234	79.9145	 -4.486092   -3.454978  2  2
235	80.0000	 -4.334087   -2.415766  2  2
236	79.6610	 -1.547962   -1.275260  2  1
237	79.7468	 -1.105553   -1.940898  1  1
238	79.8319	 -2.553071   -2.200245  2  2
239	79.9163	 -2.048177   -1.528170  2  2
240	79.5833	 -5.075269   -5.472969  1  2
241	79.2531	 -3.956830   -4.709647  1  2
242	79.3388	 -6.049233   -5.778839  2  2
243	79.0123	 -5.536551   -5.089598  2  1
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567	79.3651	 -2.350924   -1.822873  2  2
568	79.4014	 -7.131980   -2.048010  2  2
569	79.2619	 -3.590161   -3.180804  2  1
570	79.2982	 -4.987507   -6.828916  1  1
571	79.3345	 -4.648136   -3.477847  2  2
572	79.3706	 -3.101429   -2.799841  2  2
573	79.2321	 -3.302221   -3.598333  1  2
574	79.2683	 -3.841604   -2.545219  2  2
575	79.3043	 -4.972885   -4.585293  2  2
576	79.3403	 -1.509533   -3.611198  1  1
577	79.3761	 -4.929231   -4.149185  2  2
578	79.4118	 -2.928544   -2.710951  2  2
579	79.2746	 -5.158258   -6.222784  1  2
580	79.3103	 -1.466761   -2.815369  1  1
581	79.3460	 -4.922784   -6.578940  1  1
582	79.3814	 -5.483848   -4.938335  2  2
583	79.4168	 -4.246953   -4.118290  2  2
584	79.4521	 -4.268123   -4.666781  1  1
585	79.4872	 -0.493039   -2.078280  1  1
586	79.5222	 -3.538867   -4.021829  1  1
587	79.3867	 -6.120214   -5.197267  2  1
588	79.2517	 -3.461265   -3.834016  1  2
589	79.2869	 -3.721417   -3.361696  2  2
590	79.3220	 -4.512615   -3.668433  2  2
591	79.3570	 -3.336484   -3.018987  2  2
592	79.3919	 -3.049153   -4.394095  1  1
593	79.4266	 -4.565744   -3.815740  2  2
594	79.4613	 -3.922968   -4.874240  1  1
595	79.4958	 -2.036466   -1.962602  2  2
596	79.5302	 -4.407050   -4.254406  2  2
597	79.3970	 -2.228508   -1.856347  2  1
598	79.4314	 -2.370530   -2.477689  1  1
599	79.4658	 -2.737822   -3.861054  1  1
600	79.5000	 -4.184027   -3.785848  2  2
601	79.3677	 -3.175785   -3.189948  1  2
602	79.4020	 -2.766632   -3.892073  1  1
603	79.4362	 -7.451322   -5.913773  2  2
604	79.4702	 -2.611948   -2.588850  2  2
605	79.3388	 -2.718398   -1.959275  2  1
606	79.3729	 -3.399919   -2.464131  2  2
607	79.4069	 -3.202816   -3.365323  1  1
608	79.4408	 -2.262888   -4.204949  1  1
609	79.4745	 -5.478354   -6.488153  1  1
610	79.5082	 -1.745849   -2.553611  1  1
611	79.5417	 -4.337313   -4.488841  1  1
612	79.5752	 -5.411940   -7.324984  1  1
613	79.4454	 -1.543220   -1.925376  1  2
614	79.4788	 -4.181530   -1.758894  2  2
615	79.5122	 -2.921239   -2.487154  2  2
616	79.3831	 -3.939924   -4.365108  1  2
617	79.4165	-12.485373   -6.299793  2  2
618	79.2880	 -3.766184   -4.025695  1  2
619	79.3215	 -4.420929   -3.387662  2  2
620	79.3548	 -3.523631   -3.821978  1  1
621	79.3881	 -4.135296   -3.810388  2  2
622	79.4212	 -2.316716   -2.385572  1  1
623	79.4543	 -2.984393   -3.125454  1  1
624	79.4872	 -5.036418   -3.711076  2  2
625	79.5200	 -3.323389   -5.095586  1  1
626	79.5527	 -2.052625   -2.523125  1  1
627	79.5853	 -3.699679   -4.210502  1  1
628	79.6178	 -2.654528   -1.421031  2  2
629	79.6502	 -1.791872   -2.645438  1  1
630	79.6825	 -0.697313   -1.167922  1  1
631	79.7147	 -1.144344   -1.641885  1  1
632	79.7468	 -2.019848   -1.454332  2  2
633	79.7788	 -2.297464   -1.482609  2  2
634	79.8107	 -2.770743   -2.995851  1  1
635	79.6850	 -4.435986   -4.523976  1  2
636	79.7170	 -1.772143   -3.428356  1  1
637	79.7488	 -2.580319   -5.174417  1  1
638	79.7806	 -5.783049   -5.791998  1  1
639	79.6557	 -1.601720   -1.279863  2  1
640	79.5312	 -1.846057   -1.854309  1  2
641	79.5632	 -6.297995   -6.336084  1  1
642	79.5950	 -4.627083   -2.367408  2  2
643	79.6267	 -1.587595   -0.608102  2  2
644	79.6584	 -3.617431   -5.555645  1  1
645	79.6899	 -0.398291   -2.167088  1  1
646	79.5666	 -4.090449   -3.860139  2  1
647	79.4436	 -5.316422   -4.226013  2  1
648	79.3210	 -2.893789   -3.325147  1  2
649	79.3529	 -2.637421   -3.389922  1  1
650	79.3846	 -4.771074   -5.009512  1  1
651	79.4163	 -7.244587   -6.908064  2  2
652	79.4479	 -5.672418   -4.930308  2  2
653	79.4793	 -6.282917   -5.682921  2  2
654	79.3578	 -4.125629   -4.968382  1  2
655	79.2366	 -2.422593   -2.801785  1  2
656	79.2683	 -5.853437   -1.939471  2  2
657	79.1476	 -6.096133   -6.426961  1  2
658	79.1793	 -3.951044   -2.699911  2  2
659	79.2109	 -2.764668   -1.701965  2  2
660	79.2424	 -2.781962   -2.284799  2  2
661	79.2738	 -3.409875   -3.552336  1  1
662	79.3051	 -3.688469   -4.350732  1  1
663	79.3363	 -8.155697   -8.128558  2  2
664	79.2169	 -2.779032   -2.683542  2  1
665	79.0977	 -2.782017   -2.814994  1  2
666	79.1291	 -5.190616   -6.289677  1  1
667	79.0105	 -3.081096  -13.205381  1  2
668	79.0419	 -1.779173   -2.425452  1  1
669	79.0732	 -2.416049   -3.614475  1  1
670	78.9552	 -2.998945   -2.714765  2  1
671	78.9866	 -2.681998   -4.456591  1  1
672	78.8690	 -3.358626   -3.395876  1  2
673	78.9004	 -2.224485   -1.958519  2  2
674	78.7834	 -6.491204   -5.796781  2  1
675	78.6667	 -3.931536   -3.079154  2  1
676	78.5503	 -2.276906   -3.060068  1  2
677	78.5820	 -2.585131   -3.314287  1  1
678	78.4661	 -4.942374   -5.210808  1  2
679	78.3505	 -4.439645   -5.018248  1  2
680	78.3824	 -3.282007   -4.414443  1  1
681	78.2673	 -3.078207   -2.675522  2  1
682	78.2991	 -2.934058   -2.484721  2  2
683	78.3309	 -1.290468   -2.057258  1  1
684	78.3626	 -4.214497   -6.005731  1  1
685	78.3942	 -3.112467   -1.886591  2  2
686	78.4257	 -5.079035   -4.743478  2  2
687	78.4571	 -3.507342   -1.968972  2  2
688	78.4884	 -8.454294   -8.691545  1  1
689	78.5196	 -2.714880   -1.573002  2  2
690	78.4058	 -3.136971   -3.441158  1  2
691	78.2923	 -3.791540   -3.289162  2  1
692	78.3237	 -1.427797   -3.511649  1  1
693	78.3550	 -3.931297   -4.172843  1  1
694	78.2421	 -3.169856   -3.256739  1  2
695	78.1295	 -5.083444   -4.736279  2  1
696	78.0172	 -6.098144   -5.164058  2  1
697	78.0488	 -2.062809   -2.370212  1  1
698	77.9370	 -4.536262   -4.639502  1  2
699	77.9685	 -3.526263   -5.444867  1  1
700	78.0000	 -3.883863   -3.459682  2  2
701	77.8887	 -2.105535   -1.916630  2  1
702	77.7778	 -4.780732   -5.394495  1  2
703	77.6671	 -2.505935   -2.335628  2  1
704	77.6989	 -1.169973   -2.095141  1  1
705	77.7305	 -2.659179   -2.229764  2  2
706	77.7620	 -2.884037   -2.532696  2  2
707	77.7935	 -5.512810   -5.547718  1  1
708	77.8249	 -2.586272   -2.225019  2  2
709	77.8561	 -1.895538   -1.506039  2  2
710	77.8873	 -2.473443   -2.913836  1  1
711	77.7778	 -2.224890   -2.387285  1  2
712	77.6685	 -3.589169   -4.771236  1  2
713	77.5596	 -2.738242   -3.322938  1  2
714	77.5910	 -2.912599   -2.463630  2  2
715	77.6224	 -5.103544   -4.192664  2  2
716	77.6536	 -5.042183   -4.479640  2  2
717	77.6848	 -2.939737   -0.230763  2  2
718	77.7159	 -3.398472   -5.732434  1  1
719	77.7469	 -4.872331   -5.266692  1  1
720	77.6389	 -0.904538   -4.944103  1  2
721	77.5312	 -4.538811   -5.007440  1  2
722	77.4238	 -2.398450   -1.954020  2  1
723	77.4550	 -2.600455   -3.203215  1  1
724	77.3481	 -3.821189   -4.061665  1  2
725	77.2414	 -3.186985   -3.450117  1  2
726	77.1350	 -3.506958   -3.726928  1  2
727	77.1664	 -3.277593   -2.608145  2  2
728	77.1978	 -2.765378   -3.560674  1  1
729	77.2291	 -1.383639   -3.035660  1  1
730	77.1233	 -3.365168   -3.250345  2  1
731	77.1546	 -1.406738   -2.678038  1  1
732	77.1858	 -3.086398   -2.621191  2  2
733	77.2169	 -5.179922   -4.321307  2  2
734	77.2480	 -0.052789  -13.799755  1  1
735	77.1429	 -3.389907   -3.290798  2  1
736	77.1739	 -2.094019   -2.756590  1  1
737	77.2049	 -3.922629   -4.086463  1  1
738	77.2358	 -4.839579   -4.703310  2  2
739	77.2666	 -0.112841  -13.733483  1  1
740	77.2973	 -3.738626   -3.245718  2  2
741	77.3279	 -4.874781   -5.020857  1  1
742	77.3585	 -3.287271   -1.881432  2  2
743	77.3890	 -3.963702   -3.463186  2  2
744	77.4194	 -3.798737   -2.622459  2  2
745	77.4497	 -3.329896   -4.581595  1  1
746	77.4799	 -4.801835   -5.278326  1  1
747	77.5100	 -4.285132   -6.274912  1  1
748	77.5401	 -3.818437   -3.380208  2  2
749	77.5701	 -3.403507   -4.424786  1  1
750	77.6000	 -0.615882  -16.180925  1  1

Final Winogrande score(750 tasks): 77.6000 +/- 1.5234