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1 |
+
---
|
2 |
+
license: cc-by-nc-4.0
|
3 |
+
language:
|
4 |
+
- ro
|
5 |
+
base_model: OpenLLM-Ro/RoLlama3-8b-Instruct-2024-06-28
|
6 |
+
datasets:
|
7 |
+
- OpenLLM-Ro/ro_sft_alpaca
|
8 |
+
- OpenLLM-Ro/ro_sft_alpaca_gpt4
|
9 |
+
- OpenLLM-Ro/ro_sft_dolly
|
10 |
+
- OpenLLM-Ro/ro_sft_selfinstruct_gpt4
|
11 |
+
- OpenLLM-Ro/ro_sft_norobots
|
12 |
+
- OpenLLM-Ro/ro_sft_orca
|
13 |
+
- OpenLLM-Ro/ro_sft_camel
|
14 |
+
tags:
|
15 |
+
- llama-cpp
|
16 |
+
- gguf-my-repo
|
17 |
+
model-index:
|
18 |
+
- name: OpenLLM-Ro/RoLlama3-8b-Instruct-2024-06-28
|
19 |
+
results:
|
20 |
+
- task:
|
21 |
+
type: text-generation
|
22 |
+
dataset:
|
23 |
+
name: RoMT-Bench
|
24 |
+
type: RoMT-Bench
|
25 |
+
metrics:
|
26 |
+
- type: Score
|
27 |
+
value: 5.15
|
28 |
+
name: Score
|
29 |
+
- type: Score
|
30 |
+
value: 6.03
|
31 |
+
name: First turn
|
32 |
+
- type: Score
|
33 |
+
value: 4.28
|
34 |
+
name: Second turn
|
35 |
+
- task:
|
36 |
+
type: text-generation
|
37 |
+
dataset:
|
38 |
+
name: RoCulturaBench
|
39 |
+
type: RoCulturaBench
|
40 |
+
metrics:
|
41 |
+
- type: Score
|
42 |
+
value: 3.71
|
43 |
+
name: Score
|
44 |
+
- task:
|
45 |
+
type: text-generation
|
46 |
+
dataset:
|
47 |
+
name: Romanian_Academic_Benchmarks
|
48 |
+
type: Romanian_Academic_Benchmarks
|
49 |
+
metrics:
|
50 |
+
- type: accuracy
|
51 |
+
value: 50.56
|
52 |
+
name: Average accuracy
|
53 |
+
- task:
|
54 |
+
type: text-generation
|
55 |
+
dataset:
|
56 |
+
name: OpenLLM-Ro/ro_arc_challenge
|
57 |
+
type: OpenLLM-Ro/ro_arc_challenge
|
58 |
+
metrics:
|
59 |
+
- type: accuracy
|
60 |
+
value: 44.7
|
61 |
+
name: Average accuracy
|
62 |
+
- type: accuracy
|
63 |
+
value: 41.9
|
64 |
+
name: 0-shot
|
65 |
+
- type: accuracy
|
66 |
+
value: 44.3
|
67 |
+
name: 1-shot
|
68 |
+
- type: accuracy
|
69 |
+
value: 44.56
|
70 |
+
name: 3-shot
|
71 |
+
- type: accuracy
|
72 |
+
value: 45.5
|
73 |
+
name: 5-shot
|
74 |
+
- type: accuracy
|
75 |
+
value: 46.1
|
76 |
+
name: 10-shot
|
77 |
+
- type: accuracy
|
78 |
+
value: 45.84
|
79 |
+
name: 25-shot
|
80 |
+
- task:
|
81 |
+
type: text-generation
|
82 |
+
dataset:
|
83 |
+
name: OpenLLM-Ro/ro_mmlu
|
84 |
+
type: OpenLLM-Ro/ro_mmlu
|
85 |
+
metrics:
|
86 |
+
- type: accuracy
|
87 |
+
value: 52.19
|
88 |
+
name: Average accuracy
|
89 |
+
- type: accuracy
|
90 |
+
value: 50.85
|
91 |
+
name: 0-shot
|
92 |
+
- type: accuracy
|
93 |
+
value: 51.24
|
94 |
+
name: 1-shot
|
95 |
+
- type: accuracy
|
96 |
+
value: 53.3
|
97 |
+
name: 3-shot
|
98 |
+
- type: accuracy
|
99 |
+
value: 53.39
|
100 |
+
name: 5-shot
|
101 |
+
- task:
|
102 |
+
type: text-generation
|
103 |
+
dataset:
|
104 |
+
name: OpenLLM-Ro/ro_winogrande
|
105 |
+
type: OpenLLM-Ro/ro_winogrande
|
106 |
+
metrics:
|
107 |
+
- type: accuracy
|
108 |
+
value: 67.23
|
109 |
+
name: Average accuracy
|
110 |
+
- type: accuracy
|
111 |
+
value: 65.19
|
112 |
+
name: 0-shot
|
113 |
+
- type: accuracy
|
114 |
+
value: 66.54
|
115 |
+
name: 1-shot
|
116 |
+
- type: accuracy
|
117 |
+
value: 67.88
|
118 |
+
name: 3-shot
|
119 |
+
- type: accuracy
|
120 |
+
value: 69.3
|
121 |
+
name: 5-shot
|
122 |
+
- task:
|
123 |
+
type: text-generation
|
124 |
+
dataset:
|
125 |
+
name: OpenLLM-Ro/ro_hellaswag
|
126 |
+
type: OpenLLM-Ro/ro_hellaswag
|
127 |
+
metrics:
|
128 |
+
- type: accuracy
|
129 |
+
value: 57.69
|
130 |
+
name: Average accuracy
|
131 |
+
- type: accuracy
|
132 |
+
value: 56.12
|
133 |
+
name: 0-shot
|
134 |
+
- type: accuracy
|
135 |
+
value: 57.37
|
136 |
+
name: 1-shot
|
137 |
+
- type: accuracy
|
138 |
+
value: 57.92
|
139 |
+
name: 3-shot
|
140 |
+
- type: accuracy
|
141 |
+
value: 58.18
|
142 |
+
name: 5-shot
|
143 |
+
- type: accuracy
|
144 |
+
value: 58.85
|
145 |
+
name: 10-shot
|
146 |
+
- task:
|
147 |
+
type: text-generation
|
148 |
+
dataset:
|
149 |
+
name: OpenLLM-Ro/ro_gsm8k
|
150 |
+
type: OpenLLM-Ro/ro_gsm8k
|
151 |
+
metrics:
|
152 |
+
- type: accuracy
|
153 |
+
value: 30.23
|
154 |
+
name: Average accuracy
|
155 |
+
- type: accuracy
|
156 |
+
value: 29.42
|
157 |
+
name: 1-shot
|
158 |
+
- type: accuracy
|
159 |
+
value: 30.02
|
160 |
+
name: 3-shot
|
161 |
+
- type: accuracy
|
162 |
+
value: 31.24
|
163 |
+
name: 5-shot
|
164 |
+
- task:
|
165 |
+
type: text-generation
|
166 |
+
dataset:
|
167 |
+
name: OpenLLM-Ro/ro_truthfulqa
|
168 |
+
type: OpenLLM-Ro/ro_truthfulqa
|
169 |
+
metrics:
|
170 |
+
- type: accuracy
|
171 |
+
value: 51.34
|
172 |
+
name: Average accuracy
|
173 |
+
- task:
|
174 |
+
type: text-generation
|
175 |
+
dataset:
|
176 |
+
name: LaRoSeDa_binary
|
177 |
+
type: LaRoSeDa_binary
|
178 |
+
metrics:
|
179 |
+
- type: macro-f1
|
180 |
+
value: 97.52
|
181 |
+
name: Average macro-f1
|
182 |
+
- type: macro-f1
|
183 |
+
value: 97.43
|
184 |
+
name: 0-shot
|
185 |
+
- type: macro-f1
|
186 |
+
value: 96.6
|
187 |
+
name: 1-shot
|
188 |
+
- type: macro-f1
|
189 |
+
value: 97.9
|
190 |
+
name: 3-shot
|
191 |
+
- type: macro-f1
|
192 |
+
value: 98.13
|
193 |
+
name: 5-shot
|
194 |
+
- task:
|
195 |
+
type: text-generation
|
196 |
+
dataset:
|
197 |
+
name: LaRoSeDa_multiclass
|
198 |
+
type: LaRoSeDa_multiclass
|
199 |
+
metrics:
|
200 |
+
- type: macro-f1
|
201 |
+
value: 67.41
|
202 |
+
name: Average macro-f1
|
203 |
+
- type: macro-f1
|
204 |
+
value: 63.77
|
205 |
+
name: 0-shot
|
206 |
+
- type: macro-f1
|
207 |
+
value: 68.91
|
208 |
+
name: 1-shot
|
209 |
+
- type: macro-f1
|
210 |
+
value: 66.36
|
211 |
+
name: 3-shot
|
212 |
+
- type: macro-f1
|
213 |
+
value: 70.61
|
214 |
+
name: 5-shot
|
215 |
+
- task:
|
216 |
+
type: text-generation
|
217 |
+
dataset:
|
218 |
+
name: LaRoSeDa_binary_finetuned
|
219 |
+
type: LaRoSeDa_binary_finetuned
|
220 |
+
metrics:
|
221 |
+
- type: macro-f1
|
222 |
+
value: 94.15
|
223 |
+
name: Average macro-f1
|
224 |
+
- task:
|
225 |
+
type: text-generation
|
226 |
+
dataset:
|
227 |
+
name: LaRoSeDa_multiclass_finetuned
|
228 |
+
type: LaRoSeDa_multiclass_finetuned
|
229 |
+
metrics:
|
230 |
+
- type: macro-f1
|
231 |
+
value: 87.13
|
232 |
+
name: Average macro-f1
|
233 |
+
- task:
|
234 |
+
type: text-generation
|
235 |
+
dataset:
|
236 |
+
name: WMT_EN-RO
|
237 |
+
type: WMT_EN-RO
|
238 |
+
metrics:
|
239 |
+
- type: bleu
|
240 |
+
value: 24.01
|
241 |
+
name: Average bleu
|
242 |
+
- type: bleu
|
243 |
+
value: 6.92
|
244 |
+
name: 0-shot
|
245 |
+
- type: bleu
|
246 |
+
value: 29.33
|
247 |
+
name: 1-shot
|
248 |
+
- type: bleu
|
249 |
+
value: 29.79
|
250 |
+
name: 3-shot
|
251 |
+
- type: bleu
|
252 |
+
value: 30.02
|
253 |
+
name: 5-shot
|
254 |
+
- task:
|
255 |
+
type: text-generation
|
256 |
+
dataset:
|
257 |
+
name: WMT_RO-EN
|
258 |
+
type: WMT_RO-EN
|
259 |
+
metrics:
|
260 |
+
- type: bleu
|
261 |
+
value: 27.36
|
262 |
+
name: Average bleu
|
263 |
+
- type: bleu
|
264 |
+
value: 4.5
|
265 |
+
name: 0-shot
|
266 |
+
- type: bleu
|
267 |
+
value: 30.3
|
268 |
+
name: 1-shot
|
269 |
+
- type: bleu
|
270 |
+
value: 36.96
|
271 |
+
name: 3-shot
|
272 |
+
- type: bleu
|
273 |
+
value: 37.7
|
274 |
+
name: 5-shot
|
275 |
+
- task:
|
276 |
+
type: text-generation
|
277 |
+
dataset:
|
278 |
+
name: WMT_EN-RO_finetuned
|
279 |
+
type: WMT_EN-RO_finetuned
|
280 |
+
metrics:
|
281 |
+
- type: bleu
|
282 |
+
value: 26.53
|
283 |
+
name: Average bleu
|
284 |
+
- task:
|
285 |
+
type: text-generation
|
286 |
+
dataset:
|
287 |
+
name: WMT_RO-EN_finetuned
|
288 |
+
type: WMT_RO-EN_finetuned
|
289 |
+
metrics:
|
290 |
+
- type: bleu
|
291 |
+
value: 40.36
|
292 |
+
name: Average bleu
|
293 |
+
- task:
|
294 |
+
type: text-generation
|
295 |
+
dataset:
|
296 |
+
name: XQuAD
|
297 |
+
type: XQuAD
|
298 |
+
metrics:
|
299 |
+
- type: exact_match
|
300 |
+
value: 39.43
|
301 |
+
name: Average exact_match
|
302 |
+
- type: f1
|
303 |
+
value: 59.5
|
304 |
+
name: Average f1
|
305 |
+
- task:
|
306 |
+
type: text-generation
|
307 |
+
dataset:
|
308 |
+
name: XQuAD_finetuned
|
309 |
+
type: XQuAD_finetuned
|
310 |
+
metrics:
|
311 |
+
- type: exact_match
|
312 |
+
value: 44.45
|
313 |
+
name: Average exact_match
|
314 |
+
- type: f1
|
315 |
+
value: 59.76
|
316 |
+
name: Average f1
|
317 |
+
- task:
|
318 |
+
type: text-generation
|
319 |
+
dataset:
|
320 |
+
name: STS
|
321 |
+
type: STS
|
322 |
+
metrics:
|
323 |
+
- type: spearman
|
324 |
+
value: 77.2
|
325 |
+
name: Average spearman
|
326 |
+
- type: pearson
|
327 |
+
value: 77.87
|
328 |
+
name: Average pearson
|
329 |
+
- task:
|
330 |
+
type: text-generation
|
331 |
+
dataset:
|
332 |
+
name: STS_finetuned
|
333 |
+
type: STS_finetuned
|
334 |
+
metrics:
|
335 |
+
- type: spearman
|
336 |
+
value: 85.8
|
337 |
+
name: Average spearman
|
338 |
+
- type: pearson
|
339 |
+
value: 86.05
|
340 |
+
name: Average pearson
|
341 |
+
- task:
|
342 |
+
type: text-generation
|
343 |
+
dataset:
|
344 |
+
name: XQuAD_EM
|
345 |
+
type: XQuAD_EM
|
346 |
+
metrics:
|
347 |
+
- type: exact_match
|
348 |
+
value: 4.45
|
349 |
+
name: 0-shot
|
350 |
+
- type: exact_match
|
351 |
+
value: 48.24
|
352 |
+
name: 1-shot
|
353 |
+
- type: exact_match
|
354 |
+
value: 52.03
|
355 |
+
name: 3-shot
|
356 |
+
- type: exact_match
|
357 |
+
value: 53.03
|
358 |
+
name: 5-shot
|
359 |
+
- task:
|
360 |
+
type: text-generation
|
361 |
+
dataset:
|
362 |
+
name: XQuAD_F1
|
363 |
+
type: XQuAD_F1
|
364 |
+
metrics:
|
365 |
+
- type: f1
|
366 |
+
value: 26.08
|
367 |
+
name: 0-shot
|
368 |
+
- type: f1
|
369 |
+
value: 68.4
|
370 |
+
name: 1-shot
|
371 |
+
- type: f1
|
372 |
+
value: 71.92
|
373 |
+
name: 3-shot
|
374 |
+
- type: f1
|
375 |
+
value: 71.6
|
376 |
+
name: 5-shot
|
377 |
+
- task:
|
378 |
+
type: text-generation
|
379 |
+
dataset:
|
380 |
+
name: STS_Spearman
|
381 |
+
type: STS_Spearman
|
382 |
+
metrics:
|
383 |
+
- type: spearman
|
384 |
+
value: 77.76
|
385 |
+
name: 1-shot
|
386 |
+
- type: spearman
|
387 |
+
value: 76.72
|
388 |
+
name: 3-shot
|
389 |
+
- type: spearman
|
390 |
+
value: 77.12
|
391 |
+
name: 5-shot
|
392 |
+
- task:
|
393 |
+
type: text-generation
|
394 |
+
dataset:
|
395 |
+
name: STS_Pearson
|
396 |
+
type: STS_Pearson
|
397 |
+
metrics:
|
398 |
+
- type: pearson
|
399 |
+
value: 77.83
|
400 |
+
name: 1-shot
|
401 |
+
- type: pearson
|
402 |
+
value: 77.64
|
403 |
+
name: 3-shot
|
404 |
+
- type: pearson
|
405 |
+
value: 78.13
|
406 |
+
name: 5-shot
|
407 |
+
---
|
408 |
+
|
409 |
+
# vladciocan88/RoLlama3-8b-Instruct-2024-06-28-Q8_0-GGUF
|
410 |
+
This model was converted to GGUF format from [`OpenLLM-Ro/RoLlama3-8b-Instruct-2024-06-28`](https://huggingface.co/OpenLLM-Ro/RoLlama3-8b-Instruct-2024-06-28) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
|
411 |
+
Refer to the [original model card](https://huggingface.co/OpenLLM-Ro/RoLlama3-8b-Instruct-2024-06-28) for more details on the model.
|
412 |
+
|
413 |
+
## Use with llama.cpp
|
414 |
+
Install llama.cpp through brew (works on Mac and Linux)
|
415 |
+
|
416 |
+
```bash
|
417 |
+
brew install llama.cpp
|
418 |
+
|
419 |
+
```
|
420 |
+
Invoke the llama.cpp server or the CLI.
|
421 |
+
|
422 |
+
### CLI:
|
423 |
+
```bash
|
424 |
+
llama-cli --hf-repo vladciocan88/RoLlama3-8b-Instruct-2024-06-28-Q8_0-GGUF --hf-file rollama3-8b-instruct-2024-06-28-q8_0.gguf -p "The meaning to life and the universe is"
|
425 |
+
```
|
426 |
+
|
427 |
+
### Server:
|
428 |
+
```bash
|
429 |
+
llama-server --hf-repo vladciocan88/RoLlama3-8b-Instruct-2024-06-28-Q8_0-GGUF --hf-file rollama3-8b-instruct-2024-06-28-q8_0.gguf -c 2048
|
430 |
+
```
|
431 |
+
|
432 |
+
Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.
|
433 |
+
|
434 |
+
Step 1: Clone llama.cpp from GitHub.
|
435 |
+
```
|
436 |
+
git clone https://github.com/ggerganov/llama.cpp
|
437 |
+
```
|
438 |
+
|
439 |
+
Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
|
440 |
+
```
|
441 |
+
cd llama.cpp && LLAMA_CURL=1 make
|
442 |
+
```
|
443 |
+
|
444 |
+
Step 3: Run inference through the main binary.
|
445 |
+
```
|
446 |
+
./llama-cli --hf-repo vladciocan88/RoLlama3-8b-Instruct-2024-06-28-Q8_0-GGUF --hf-file rollama3-8b-instruct-2024-06-28-q8_0.gguf -p "The meaning to life and the universe is"
|
447 |
+
```
|
448 |
+
or
|
449 |
+
```
|
450 |
+
./llama-server --hf-repo vladciocan88/RoLlama3-8b-Instruct-2024-06-28-Q8_0-GGUF --hf-file rollama3-8b-instruct-2024-06-28-q8_0.gguf -c 2048
|
451 |
+
```
|