dh-mc commited on
Commit
6702142
1 Parent(s): 68936f4

ref code from novel-translation

Browse files
.gitattributes CHANGED
@@ -33,3 +33,10 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
33
  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
 
 
 
 
 
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
36
+ datasets/mgtv/ filter=lfs diff=lfs merge=lfs -text
37
+ datasets/mgtv/dev.csv filter=lfs diff=lfs merge=lfs -text
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+ datasets/mgtv/test_a.csv filter=lfs diff=lfs merge=lfs -text
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+ datasets/mgtv/train.csv filter=lfs diff=lfs merge=lfs -text
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+ results/mac-results-colab.csv filter=lfs diff=lfs merge=lfs -text
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+ results/mac-results-colab.gsheet filter=lfs diff=lfs merge=lfs -text
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+ results/mac-results_lf.csv filter=lfs diff=lfs merge=lfs -text
competition/01_EDA.ipynb ADDED
The diff for this file is too large to render. See raw diff
 
config/qwen2_0.5b_lora_sft.yaml ADDED
@@ -0,0 +1,39 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ### model
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+ model_name_or_path: Qwen/Qwen2-0.5B-Instruct
3
+
4
+ ### method
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+ stage: sft
6
+ do_train: true
7
+ finetuning_type: lora
8
+ lora_target: all
9
+
10
+ ### dataset
11
+ dataset: alpaca_mac
12
+ template: chatml
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+ cutoff_len: 1024
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+ max_samples: 4528
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+ overwrite_cache: true
16
+ preprocessing_num_workers: 16
17
+
18
+ ### output
19
+ output_dir: saves/qwen2-0.5b/lora/sft
20
+ logging_steps: 10
21
+ save_steps: 560
22
+ plot_loss: true
23
+ overwrite_output_dir: true
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+
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+ ### train
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+ per_device_train_batch_size: 1
27
+ gradient_accumulation_steps: 8
28
+ learning_rate: 1.0e-4
29
+ num_train_epochs: 10.0
30
+ lr_scheduler_type: cosine
31
+ warmup_ratio: 0.1
32
+ bf16: true
33
+ ddp_timeout: 180000000
34
+
35
+ ### eval
36
+ val_size: 0.01
37
+ per_device_eval_batch_size: 1
38
+ eval_strategy: steps
39
+ eval_steps: 560
config/qwen2_1.5b_lora_sft.yaml ADDED
@@ -0,0 +1,39 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ### model
2
+ model_name_or_path: Qwen/Qwen2-1.5B-Instruct
3
+
4
+ ### method
5
+ stage: sft
6
+ do_train: true
7
+ finetuning_type: lora
8
+ lora_target: all
9
+
10
+ ### dataset
11
+ dataset: alpaca_mac
12
+ template: chatml
13
+ cutoff_len: 1024
14
+ max_samples: 4528
15
+ overwrite_cache: true
16
+ preprocessing_num_workers: 16
17
+
18
+ ### output
19
+ output_dir: saves/qwen2-1.5b/lora/sft
20
+ logging_steps: 10
21
+ save_steps: 560
22
+ plot_loss: true
23
+ overwrite_output_dir: true
24
+
25
+ ### train
26
+ per_device_train_batch_size: 1
27
+ gradient_accumulation_steps: 8
28
+ learning_rate: 1.0e-4
29
+ num_train_epochs: 10.0
30
+ lr_scheduler_type: cosine
31
+ warmup_ratio: 0.1
32
+ bf16: true
33
+ ddp_timeout: 180000000
34
+
35
+ ### eval
36
+ val_size: 0.01
37
+ per_device_eval_batch_size: 1
38
+ eval_strategy: steps
39
+ eval_steps: 560
config/qwen2_7b_lora_sft.yaml ADDED
@@ -0,0 +1,39 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ### model
2
+ model_name_or_path: Qwen/Qwen2-7B-Instruct
3
+
4
+ ### method
5
+ stage: sft
6
+ do_train: true
7
+ finetuning_type: lora
8
+ lora_target: all
9
+
10
+ ### dataset
11
+ dataset: alpaca_mac
12
+ template: chatml
13
+ cutoff_len: 1024
14
+ max_samples: 4528
15
+ overwrite_cache: true
16
+ preprocessing_num_workers: 16
17
+
18
+ ### output
19
+ output_dir: saves/qwen2-7b/lora/sft
20
+ logging_steps: 10
21
+ save_steps: 560
22
+ plot_loss: true
23
+ overwrite_output_dir: true
24
+
25
+ ### train
26
+ per_device_train_batch_size: 1
27
+ gradient_accumulation_steps: 8
28
+ learning_rate: 1.0e-4
29
+ num_train_epochs: 10.0
30
+ lr_scheduler_type: cosine
31
+ warmup_ratio: 0.1
32
+ bf16: true
33
+ ddp_timeout: 180000000
34
+
35
+ ### eval
36
+ val_size: 0.01
37
+ per_device_eval_batch_size: 1
38
+ eval_strategy: steps
39
+ eval_steps: 560
data/alpaca_mac.json ADDED
The diff for this file is too large to render. See raw diff
 
data/dataset_info.json ADDED
@@ -0,0 +1,568 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpaca_mac": {
3
+ "file_name": "alpaca_mac.json"
4
+ },
5
+ "identity": {
6
+ "file_name": "identity.json"
7
+ },
8
+ "alpaca_en_demo": {
9
+ "file_name": "alpaca_en_demo.json"
10
+ },
11
+ "alpaca_zh_demo": {
12
+ "file_name": "alpaca_zh_demo.json"
13
+ },
14
+ "glaive_toolcall_en_demo": {
15
+ "file_name": "glaive_toolcall_en_demo.json",
16
+ "formatting": "sharegpt",
17
+ "columns": {
18
+ "messages": "conversations",
19
+ "tools": "tools"
20
+ }
21
+ },
22
+ "glaive_toolcall_zh_demo": {
23
+ "file_name": "glaive_toolcall_zh_demo.json",
24
+ "formatting": "sharegpt",
25
+ "columns": {
26
+ "messages": "conversations",
27
+ "tools": "tools"
28
+ }
29
+ },
30
+ "mllm_demo": {
31
+ "file_name": "mllm_demo.json",
32
+ "formatting": "sharegpt",
33
+ "columns": {
34
+ "messages": "messages",
35
+ "images": "images"
36
+ },
37
+ "tags": {
38
+ "role_tag": "role",
39
+ "content_tag": "content",
40
+ "user_tag": "user",
41
+ "assistant_tag": "assistant"
42
+ }
43
+ },
44
+ "alpaca_en": {
45
+ "hf_hub_url": "llamafactory/alpaca_en",
46
+ "ms_hub_url": "llamafactory/alpaca_en"
47
+ },
48
+ "alpaca_zh": {
49
+ "hf_hub_url": "llamafactory/alpaca_zh",
50
+ "ms_hub_url": "llamafactory/alpaca_zh"
51
+ },
52
+ "alpaca_gpt4_en": {
53
+ "hf_hub_url": "llamafactory/alpaca_gpt4_en",
54
+ "ms_hub_url": "llamafactory/alpaca_gpt4_en"
55
+ },
56
+ "alpaca_gpt4_zh": {
57
+ "hf_hub_url": "llamafactory/alpaca_gpt4_zh",
58
+ "ms_hub_url": "llamafactory/alpaca_gpt4_zh"
59
+ },
60
+ "glaive_toolcall_en": {
61
+ "hf_hub_url": "llamafactory/glaive_toolcall_en",
62
+ "formatting": "sharegpt",
63
+ "columns": {
64
+ "messages": "conversations",
65
+ "tools": "tools"
66
+ }
67
+ },
68
+ "glaive_toolcall_zh": {
69
+ "hf_hub_url": "llamafactory/glaive_toolcall_zh",
70
+ "formatting": "sharegpt",
71
+ "columns": {
72
+ "messages": "conversations",
73
+ "tools": "tools"
74
+ }
75
+ },
76
+ "lima": {
77
+ "hf_hub_url": "llamafactory/lima",
78
+ "formatting": "sharegpt"
79
+ },
80
+ "guanaco": {
81
+ "hf_hub_url": "JosephusCheung/GuanacoDataset",
82
+ "ms_hub_url": "AI-ModelScope/GuanacoDataset"
83
+ },
84
+ "belle_2m": {
85
+ "hf_hub_url": "BelleGroup/train_2M_CN",
86
+ "ms_hub_url": "AI-ModelScope/train_2M_CN"
87
+ },
88
+ "belle_1m": {
89
+ "hf_hub_url": "BelleGroup/train_1M_CN",
90
+ "ms_hub_url": "AI-ModelScope/train_1M_CN"
91
+ },
92
+ "belle_0.5m": {
93
+ "hf_hub_url": "BelleGroup/train_0.5M_CN",
94
+ "ms_hub_url": "AI-ModelScope/train_0.5M_CN"
95
+ },
96
+ "belle_dialog": {
97
+ "hf_hub_url": "BelleGroup/generated_chat_0.4M",
98
+ "ms_hub_url": "AI-ModelScope/generated_chat_0.4M"
99
+ },
100
+ "belle_math": {
101
+ "hf_hub_url": "BelleGroup/school_math_0.25M",
102
+ "ms_hub_url": "AI-ModelScope/school_math_0.25M"
103
+ },
104
+ "belle_multiturn": {
105
+ "script_url": "belle_multiturn",
106
+ "formatting": "sharegpt"
107
+ },
108
+ "ultra_chat": {
109
+ "script_url": "ultra_chat",
110
+ "formatting": "sharegpt"
111
+ },
112
+ "open_platypus": {
113
+ "hf_hub_url": "garage-bAInd/Open-Platypus",
114
+ "ms_hub_url": "AI-ModelScope/Open-Platypus"
115
+ },
116
+ "codealpaca": {
117
+ "hf_hub_url": "sahil2801/CodeAlpaca-20k",
118
+ "ms_hub_url": "AI-ModelScope/CodeAlpaca-20k"
119
+ },
120
+ "alpaca_cot": {
121
+ "hf_hub_url": "QingyiSi/Alpaca-CoT",
122
+ "ms_hub_url": "AI-ModelScope/Alpaca-CoT"
123
+ },
124
+ "openorca": {
125
+ "hf_hub_url": "Open-Orca/OpenOrca",
126
+ "ms_hub_url": "AI-ModelScope/OpenOrca",
127
+ "columns": {
128
+ "prompt": "question",
129
+ "response": "response",
130
+ "system": "system_prompt"
131
+ }
132
+ },
133
+ "slimorca": {
134
+ "hf_hub_url": "Open-Orca/SlimOrca",
135
+ "formatting": "sharegpt"
136
+ },
137
+ "mathinstruct": {
138
+ "hf_hub_url": "TIGER-Lab/MathInstruct",
139
+ "ms_hub_url": "AI-ModelScope/MathInstruct",
140
+ "columns": {
141
+ "prompt": "instruction",
142
+ "response": "output"
143
+ }
144
+ },
145
+ "firefly": {
146
+ "hf_hub_url": "YeungNLP/firefly-train-1.1M",
147
+ "columns": {
148
+ "prompt": "input",
149
+ "response": "target"
150
+ }
151
+ },
152
+ "wikiqa": {
153
+ "hf_hub_url": "wiki_qa",
154
+ "columns": {
155
+ "prompt": "question",
156
+ "response": "answer"
157
+ }
158
+ },
159
+ "webqa": {
160
+ "hf_hub_url": "suolyer/webqa",
161
+ "ms_hub_url": "AI-ModelScope/webqa",
162
+ "columns": {
163
+ "prompt": "input",
164
+ "response": "output"
165
+ }
166
+ },
167
+ "webnovel": {
168
+ "hf_hub_url": "zxbsmk/webnovel_cn",
169
+ "ms_hub_url": "AI-ModelScope/webnovel_cn"
170
+ },
171
+ "nectar_sft": {
172
+ "hf_hub_url": "AstraMindAI/SFT-Nectar",
173
+ "ms_hub_url": "AI-ModelScope/SFT-Nectar"
174
+ },
175
+ "deepctrl": {
176
+ "ms_hub_url": "deepctrl/deepctrl-sft-data"
177
+ },
178
+ "adgen": {
179
+ "hf_hub_url": "HasturOfficial/adgen",
180
+ "ms_hub_url": "AI-ModelScope/adgen",
181
+ "columns": {
182
+ "prompt": "content",
183
+ "response": "summary"
184
+ }
185
+ },
186
+ "sharegpt_hyper": {
187
+ "hf_hub_url": "totally-not-an-llm/sharegpt-hyperfiltered-3k",
188
+ "formatting": "sharegpt"
189
+ },
190
+ "sharegpt4": {
191
+ "hf_hub_url": "shibing624/sharegpt_gpt4",
192
+ "ms_hub_url": "AI-ModelScope/sharegpt_gpt4",
193
+ "formatting": "sharegpt"
194
+ },
195
+ "ultrachat_200k": {
196
+ "hf_hub_url": "HuggingFaceH4/ultrachat_200k",
197
+ "ms_hub_url": "AI-ModelScope/ultrachat_200k",
198
+ "formatting": "sharegpt",
199
+ "columns": {
200
+ "messages": "messages"
201
+ },
202
+ "tags": {
203
+ "role_tag": "role",
204
+ "content_tag": "content",
205
+ "user_tag": "user",
206
+ "assistant_tag": "assistant"
207
+ }
208
+ },
209
+ "agent_instruct": {
210
+ "hf_hub_url": "THUDM/AgentInstruct",
211
+ "ms_hub_url": "ZhipuAI/AgentInstruct",
212
+ "formatting": "sharegpt"
213
+ },
214
+ "lmsys_chat": {
215
+ "hf_hub_url": "lmsys/lmsys-chat-1m",
216
+ "ms_hub_url": "AI-ModelScope/lmsys-chat-1m",
217
+ "formatting": "sharegpt",
218
+ "columns": {
219
+ "messages": "conversation"
220
+ },
221
+ "tags": {
222
+ "role_tag": "role",
223
+ "content_tag": "content",
224
+ "user_tag": "human",
225
+ "assistant_tag": "assistant"
226
+ }
227
+ },
228
+ "evol_instruct": {
229
+ "hf_hub_url": "WizardLM/WizardLM_evol_instruct_V2_196k",
230
+ "ms_hub_url": "AI-ModelScope/WizardLM_evol_instruct_V2_196k",
231
+ "formatting": "sharegpt"
232
+ },
233
+ "glaive_toolcall_100k": {
234
+ "hf_hub_url": "hiyouga/glaive-function-calling-v2-sharegpt",
235
+ "formatting": "sharegpt",
236
+ "columns": {
237
+ "messages": "conversations",
238
+ "tools": "tools"
239
+ }
240
+ },
241
+ "cosmopedia": {
242
+ "hf_hub_url": "HuggingFaceTB/cosmopedia",
243
+ "columns": {
244
+ "prompt": "prompt",
245
+ "response": "text"
246
+ }
247
+ },
248
+ "stem_zh": {
249
+ "hf_hub_url": "hfl/stem_zh_instruction"
250
+ },
251
+ "ruozhiba_gpt4": {
252
+ "hf_hub_url": "hfl/ruozhiba_gpt4_turbo"
253
+ },
254
+ "neo_sft": {
255
+ "hf_hub_url": "m-a-p/neo_sft_phase2",
256
+ "formatting": "sharegpt"
257
+ },
258
+ "magpie_pro_300k": {
259
+ "hf_hub_url": "Magpie-Align/Magpie-Pro-300K-Filtered",
260
+ "formatting": "sharegpt"
261
+ },
262
+ "web_instruct": {
263
+ "hf_hub_url": "TIGER-Lab/WebInstructSub",
264
+ "columns": {
265
+ "prompt": "question",
266
+ "response": "answer"
267
+ }
268
+ },
269
+ "llava_1k_en": {
270
+ "hf_hub_url": "BUAADreamer/llava-en-zh-2k",
271
+ "subset": "en",
272
+ "formatting": "sharegpt",
273
+ "columns": {
274
+ "messages": "messages",
275
+ "images": "images"
276
+ },
277
+ "tags": {
278
+ "role_tag": "role",
279
+ "content_tag": "content",
280
+ "user_tag": "user",
281
+ "assistant_tag": "assistant"
282
+ }
283
+ },
284
+ "llava_1k_zh": {
285
+ "hf_hub_url": "BUAADreamer/llava-en-zh-2k",
286
+ "subset": "zh",
287
+ "formatting": "sharegpt",
288
+ "columns": {
289
+ "messages": "messages",
290
+ "images": "images"
291
+ },
292
+ "tags": {
293
+ "role_tag": "role",
294
+ "content_tag": "content",
295
+ "user_tag": "user",
296
+ "assistant_tag": "assistant"
297
+ }
298
+ },
299
+ "llava_150k_en": {
300
+ "hf_hub_url": "BUAADreamer/llava-en-zh-300k",
301
+ "subset": "en",
302
+ "formatting": "sharegpt",
303
+ "columns": {
304
+ "messages": "messages",
305
+ "images": "images"
306
+ },
307
+ "tags": {
308
+ "role_tag": "role",
309
+ "content_tag": "content",
310
+ "user_tag": "user",
311
+ "assistant_tag": "assistant"
312
+ }
313
+ },
314
+ "llava_150k_zh": {
315
+ "hf_hub_url": "BUAADreamer/llava-en-zh-300k",
316
+ "subset": "zh",
317
+ "formatting": "sharegpt",
318
+ "columns": {
319
+ "messages": "messages",
320
+ "images": "images"
321
+ },
322
+ "tags": {
323
+ "role_tag": "role",
324
+ "content_tag": "content",
325
+ "user_tag": "user",
326
+ "assistant_tag": "assistant"
327
+ }
328
+ },
329
+ "mllm_pt_demo": {
330
+ "hf_hub_url": "BUAADreamer/mllm_pt_demo",
331
+ "formatting": "sharegpt",
332
+ "columns": {
333
+ "messages": "messages",
334
+ "images": "images"
335
+ },
336
+ "tags": {
337
+ "role_tag": "role",
338
+ "content_tag": "content",
339
+ "user_tag": "user",
340
+ "assistant_tag": "assistant"
341
+ }
342
+ },
343
+ "oasst_de": {
344
+ "hf_hub_url": "mayflowergmbh/oasst_de"
345
+ },
346
+ "dolly_15k_de": {
347
+ "hf_hub_url": "mayflowergmbh/dolly-15k_de"
348
+ },
349
+ "alpaca-gpt4_de": {
350
+ "hf_hub_url": "mayflowergmbh/alpaca-gpt4_de"
351
+ },
352
+ "openschnabeltier_de": {
353
+ "hf_hub_url": "mayflowergmbh/openschnabeltier_de"
354
+ },
355
+ "evol_instruct_de": {
356
+ "hf_hub_url": "mayflowergmbh/evol-instruct_de"
357
+ },
358
+ "dolphin_de": {
359
+ "hf_hub_url": "mayflowergmbh/dolphin_de"
360
+ },
361
+ "booksum_de": {
362
+ "hf_hub_url": "mayflowergmbh/booksum_de"
363
+ },
364
+ "airoboros_de": {
365
+ "hf_hub_url": "mayflowergmbh/airoboros-3.0_de"
366
+ },
367
+ "ultrachat_de": {
368
+ "hf_hub_url": "mayflowergmbh/ultra-chat_de"
369
+ },
370
+ "dpo_en_demo": {
371
+ "file_name": "dpo_en_demo.json",
372
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+ ### model
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+ ### method
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+ stage: sft
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+ ### model
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+
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+ ### method
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+ ### dataset
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+ ### eval
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+ "ultrachat_200k": {
196
+ "hf_hub_url": "HuggingFaceH4/ultrachat_200k",
197
+ "ms_hub_url": "AI-ModelScope/ultrachat_200k",
198
+ "formatting": "sharegpt",
199
+ "columns": {
200
+ "messages": "messages"
201
+ },
202
+ "tags": {
203
+ "role_tag": "role",
204
+ "content_tag": "content",
205
+ "user_tag": "user",
206
+ "assistant_tag": "assistant"
207
+ }
208
+ },
209
+ "agent_instruct": {
210
+ "hf_hub_url": "THUDM/AgentInstruct",
211
+ "ms_hub_url": "ZhipuAI/AgentInstruct",
212
+ "formatting": "sharegpt"
213
+ },
214
+ "lmsys_chat": {
215
+ "hf_hub_url": "lmsys/lmsys-chat-1m",
216
+ "ms_hub_url": "AI-ModelScope/lmsys-chat-1m",
217
+ "formatting": "sharegpt",
218
+ "columns": {
219
+ "messages": "conversation"
220
+ },
221
+ "tags": {
222
+ "role_tag": "role",
223
+ "content_tag": "content",
224
+ "user_tag": "human",
225
+ "assistant_tag": "assistant"
226
+ }
227
+ },
228
+ "evol_instruct": {
229
+ "hf_hub_url": "WizardLM/WizardLM_evol_instruct_V2_196k",
230
+ "ms_hub_url": "AI-ModelScope/WizardLM_evol_instruct_V2_196k",
231
+ "formatting": "sharegpt"
232
+ },
233
+ "glaive_toolcall_100k": {
234
+ "hf_hub_url": "hiyouga/glaive-function-calling-v2-sharegpt",
235
+ "formatting": "sharegpt",
236
+ "columns": {
237
+ "messages": "conversations",
238
+ "tools": "tools"
239
+ }
240
+ },
241
+ "cosmopedia": {
242
+ "hf_hub_url": "HuggingFaceTB/cosmopedia",
243
+ "columns": {
244
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245
+ "response": "text"
246
+ }
247
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248
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249
+ "hf_hub_url": "hfl/stem_zh_instruction"
250
+ },
251
+ "ruozhiba_gpt4": {
252
+ "hf_hub_url": "hfl/ruozhiba_gpt4_turbo"
253
+ },
254
+ "neo_sft": {
255
+ "hf_hub_url": "m-a-p/neo_sft_phase2",
256
+ "formatting": "sharegpt"
257
+ },
258
+ "magpie_pro_300k": {
259
+ "hf_hub_url": "Magpie-Align/Magpie-Pro-300K-Filtered",
260
+ "formatting": "sharegpt"
261
+ },
262
+ "web_instruct": {
263
+ "hf_hub_url": "TIGER-Lab/WebInstructSub",
264
+ "columns": {
265
+ "prompt": "question",
266
+ "response": "answer"
267
+ }
268
+ },
269
+ "llava_1k_en": {
270
+ "hf_hub_url": "BUAADreamer/llava-en-zh-2k",
271
+ "subset": "en",
272
+ "formatting": "sharegpt",
273
+ "columns": {
274
+ "messages": "messages",
275
+ "images": "images"
276
+ },
277
+ "tags": {
278
+ "role_tag": "role",
279
+ "content_tag": "content",
280
+ "user_tag": "user",
281
+ "assistant_tag": "assistant"
282
+ }
283
+ },
284
+ "llava_1k_zh": {
285
+ "hf_hub_url": "BUAADreamer/llava-en-zh-2k",
286
+ "subset": "zh",
287
+ "formatting": "sharegpt",
288
+ "columns": {
289
+ "messages": "messages",
290
+ "images": "images"
291
+ },
292
+ "tags": {
293
+ "role_tag": "role",
294
+ "content_tag": "content",
295
+ "user_tag": "user",
296
+ "assistant_tag": "assistant"
297
+ }
298
+ },
299
+ "llava_150k_en": {
300
+ "hf_hub_url": "BUAADreamer/llava-en-zh-300k",
301
+ "subset": "en",
302
+ "formatting": "sharegpt",
303
+ "columns": {
304
+ "messages": "messages",
305
+ "images": "images"
306
+ },
307
+ "tags": {
308
+ "role_tag": "role",
309
+ "content_tag": "content",
310
+ "user_tag": "user",
311
+ "assistant_tag": "assistant"
312
+ }
313
+ },
314
+ "llava_150k_zh": {
315
+ "hf_hub_url": "BUAADreamer/llava-en-zh-300k",
316
+ "subset": "zh",
317
+ "formatting": "sharegpt",
318
+ "columns": {
319
+ "messages": "messages",
320
+ "images": "images"
321
+ },
322
+ "tags": {
323
+ "role_tag": "role",
324
+ "content_tag": "content",
325
+ "user_tag": "user",
326
+ "assistant_tag": "assistant"
327
+ }
328
+ },
329
+ "mllm_pt_demo": {
330
+ "hf_hub_url": "BUAADreamer/mllm_pt_demo",
331
+ "formatting": "sharegpt",
332
+ "columns": {
333
+ "messages": "messages",
334
+ "images": "images"
335
+ },
336
+ "tags": {
337
+ "role_tag": "role",
338
+ "content_tag": "content",
339
+ "user_tag": "user",
340
+ "assistant_tag": "assistant"
341
+ }
342
+ },
343
+ "oasst_de": {
344
+ "hf_hub_url": "mayflowergmbh/oasst_de"
345
+ },
346
+ "dolly_15k_de": {
347
+ "hf_hub_url": "mayflowergmbh/dolly-15k_de"
348
+ },
349
+ "alpaca-gpt4_de": {
350
+ "hf_hub_url": "mayflowergmbh/alpaca-gpt4_de"
351
+ },
352
+ "openschnabeltier_de": {
353
+ "hf_hub_url": "mayflowergmbh/openschnabeltier_de"
354
+ },
355
+ "evol_instruct_de": {
356
+ "hf_hub_url": "mayflowergmbh/evol-instruct_de"
357
+ },
358
+ "dolphin_de": {
359
+ "hf_hub_url": "mayflowergmbh/dolphin_de"
360
+ },
361
+ "booksum_de": {
362
+ "hf_hub_url": "mayflowergmbh/booksum_de"
363
+ },
364
+ "airoboros_de": {
365
+ "hf_hub_url": "mayflowergmbh/airoboros-3.0_de"
366
+ },
367
+ "ultrachat_de": {
368
+ "hf_hub_url": "mayflowergmbh/ultra-chat_de"
369
+ },
370
+ "dpo_en_demo": {
371
+ "file_name": "dpo_en_demo.json",
372
+ "ranking": true,
373
+ "formatting": "sharegpt",
374
+ "columns": {
375
+ "messages": "conversations",
376
+ "chosen": "chosen",
377
+ "rejected": "rejected"
378
+ }
379
+ },
380
+ "dpo_zh_demo": {
381
+ "file_name": "dpo_zh_demo.json",
382
+ "ranking": true,
383
+ "formatting": "sharegpt",
384
+ "columns": {
385
+ "messages": "conversations",
386
+ "chosen": "chosen",
387
+ "rejected": "rejected"
388
+ }
389
+ },
390
+ "dpo_mix_en": {
391
+ "hf_hub_url": "hiyouga/DPO-En-Zh-20k",
392
+ "subset": "en",
393
+ "ranking": true,
394
+ "formatting": "sharegpt",
395
+ "columns": {
396
+ "messages": "conversations",
397
+ "chosen": "chosen",
398
+ "rejected": "rejected"
399
+ }
400
+ },
401
+ "dpo_mix_zh": {
402
+ "hf_hub_url": "hiyouga/DPO-En-Zh-20k",
403
+ "subset": "zh",
404
+ "ranking": true,
405
+ "formatting": "sharegpt",
406
+ "columns": {
407
+ "messages": "conversations",
408
+ "chosen": "chosen",
409
+ "rejected": "rejected"
410
+ }
411
+ },
412
+ "ultrafeedback": {
413
+ "hf_hub_url": "llamafactory/ultrafeedback_binarized",
414
+ "ms_hub_url": "llamafactory/ultrafeedback_binarized",
415
+ "ranking": true,
416
+ "columns": {
417
+ "prompt": "instruction",
418
+ "chosen": "chosen",
419
+ "rejected": "rejected"
420
+ }
421
+ },
422
+ "orca_pairs": {
423
+ "hf_hub_url": "Intel/orca_dpo_pairs",
424
+ "ranking": true,
425
+ "columns": {
426
+ "prompt": "question",
427
+ "chosen": "chosen",
428
+ "rejected": "rejected",
429
+ "system": "system"
430
+ }
431
+ },
432
+ "hh_rlhf_en": {
433
+ "script_url": "hh_rlhf_en",
434
+ "ranking": true,
435
+ "columns": {
436
+ "prompt": "instruction",
437
+ "chosen": "chosen",
438
+ "rejected": "rejected",
439
+ "history": "history"
440
+ }
441
+ },
442
+ "nectar_rm": {
443
+ "hf_hub_url": "AstraMindAI/RLAIF-Nectar",
444
+ "ms_hub_url": "AI-ModelScope/RLAIF-Nectar",
445
+ "ranking": true
446
+ },
447
+ "orca_dpo_de": {
448
+ "hf_hub_url": "mayflowergmbh/intel_orca_dpo_pairs_de",
449
+ "ranking": true
450
+ },
451
+ "kto_en_demo": {
452
+ "file_name": "kto_en_demo.json",
453
+ "formatting": "sharegpt",
454
+ "columns": {
455
+ "messages": "messages",
456
+ "kto_tag": "label"
457
+ },
458
+ "tags": {
459
+ "role_tag": "role",
460
+ "content_tag": "content",
461
+ "user_tag": "user",
462
+ "assistant_tag": "assistant"
463
+ }
464
+ },
465
+ "kto_mix_en": {
466
+ "hf_hub_url": "argilla/kto-mix-15k",
467
+ "formatting": "sharegpt",
468
+ "columns": {
469
+ "messages": "completion",
470
+ "kto_tag": "label"
471
+ },
472
+ "tags": {
473
+ "role_tag": "role",
474
+ "content_tag": "content",
475
+ "user_tag": "user",
476
+ "assistant_tag": "assistant"
477
+ }
478
+ },
479
+ "ultrafeedback_kto": {
480
+ "hf_hub_url": "argilla/ultrafeedback-binarized-preferences-cleaned-kto",
481
+ "ms_hub_url": "AI-ModelScope/ultrafeedback-binarized-preferences-cleaned-kto",
482
+ "columns": {
483
+ "prompt": "prompt",
484
+ "response": "completion",
485
+ "kto_tag": "label"
486
+ }
487
+ },
488
+ "wiki_demo": {
489
+ "file_name": "wiki_demo.txt",
490
+ "columns": {
491
+ "prompt": "text"
492
+ }
493
+ },
494
+ "c4_demo": {
495
+ "file_name": "c4_demo.json",
496
+ "columns": {
497
+ "prompt": "text"
498
+ }
499
+ },
500
+ "refinedweb": {
501
+ "hf_hub_url": "tiiuae/falcon-refinedweb",
502
+ "columns": {
503
+ "prompt": "content"
504
+ }
505
+ },
506
+ "redpajama_v2": {
507
+ "hf_hub_url": "togethercomputer/RedPajama-Data-V2",
508
+ "columns": {
509
+ "prompt": "raw_content"
510
+ },
511
+ "subset": "default"
512
+ },
513
+ "wikipedia_en": {
514
+ "hf_hub_url": "olm/olm-wikipedia-20221220",
515
+ "ms_hub_url": "AI-ModelScope/olm-wikipedia-20221220",
516
+ "columns": {
517
+ "prompt": "text"
518
+ }
519
+ },
520
+ "wikipedia_zh": {
521
+ "hf_hub_url": "pleisto/wikipedia-cn-20230720-filtered",
522
+ "ms_hub_url": "AI-ModelScope/wikipedia-cn-20230720-filtered",
523
+ "columns": {
524
+ "prompt": "completion"
525
+ }
526
+ },
527
+ "pile": {
528
+ "hf_hub_url": "monology/pile-uncopyrighted",
529
+ "ms_hub_url": "AI-ModelScope/pile",
530
+ "columns": {
531
+ "prompt": "text"
532
+ }
533
+ },
534
+ "skypile": {
535
+ "hf_hub_url": "Skywork/SkyPile-150B",
536
+ "ms_hub_url": "AI-ModelScope/SkyPile-150B",
537
+ "columns": {
538
+ "prompt": "text"
539
+ }
540
+ },
541
+ "fineweb": {
542
+ "hf_hub_url": "HuggingFaceFW/fineweb",
543
+ "columns": {
544
+ "prompt": "text"
545
+ }
546
+ },
547
+ "fineweb_edu": {
548
+ "hf_hub_url": "HuggingFaceFW/fineweb-edu",
549
+ "columns": {
550
+ "prompt": "text"
551
+ }
552
+ },
553
+ "the_stack": {
554
+ "hf_hub_url": "bigcode/the-stack",
555
+ "ms_hub_url": "AI-ModelScope/the-stack",
556
+ "columns": {
557
+ "prompt": "content"
558
+ }
559
+ },
560
+ "starcoder_python": {
561
+ "hf_hub_url": "bigcode/starcoderdata",
562
+ "ms_hub_url": "AI-ModelScope/starcoderdata",
563
+ "columns": {
564
+ "prompt": "content"
565
+ },
566
+ "folder": "python"
567
+ }
568
+ }
notebooks/01_Finetune-Llama3-with-LLaMA-Factory.ipynb ADDED
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1
+ {"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"provenance":[{"file_id":"1eRTPn37ltBbYsISy9Aw2NuI2Aq5CQrD9","timestamp":1719737717483}],"gpuType":"T4"},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"},"accelerator":"GPU"},"cells":[{"cell_type":"markdown","source":["# Finetune Llama-3 with LLaMA Factory\n","\n","Please use a **free** Tesla T4 Colab GPU to run this!\n","\n","Project homepage: https://github.com/hiyouga/LLaMA-Factory"],"metadata":{"id":"1oHFCsV0z-Jw"}},{"cell_type":"markdown","source":["## Install Dependencies"],"metadata":{"id":"lr7rB3szzhtx"}},{"cell_type":"code","execution_count":null,"metadata":{"id":"giM74oK1rRIH"},"outputs":[],"source":["%cd /content/\n","%rm -rf LLaMA-Factory\n","!git clone https://github.com/hiyouga/LLaMA-Factory.git\n","%cd LLaMA-Factory\n","%ls\n","!pip install -e .[torch,bitsandbytes]"]},{"cell_type":"markdown","source":["### Check GPU environment"],"metadata":{"id":"H9RXn_YQnn9f"}},{"cell_type":"code","source":["import torch\n","try:\n"," assert torch.cuda.is_available() is True\n","except AssertionError:\n"," print(\"Please set up a GPU before using LLaMA Factory: https://medium.com/mlearning-ai/training-yolov4-on-google-colab-316f8fff99c6\")"],"metadata":{"id":"ZkN-ktlsnrdU"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["## Update Identity Dataset"],"metadata":{"id":"TeYs5Lz-QJYk"}},{"cell_type":"code","source":["import json\n","\n","%cd /content/LLaMA-Factory/\n","\n","NAME = \"Llama-3\"\n","AUTHOR = \"LLaMA Factory\"\n","\n","with open(\"data/identity.json\", \"r\", encoding=\"utf-8\") as f:\n"," dataset = json.load(f)\n","\n","for sample in dataset:\n"," sample[\"output\"] = sample[\"output\"].replace(\"{{\"+ \"name\" + \"}}\", NAME).replace(\"{{\"+ \"author\" + \"}}\", AUTHOR)\n","\n","with open(\"data/identity.json\", \"w\", encoding=\"utf-8\") as f:\n"," json.dump(dataset, f, indent=2, ensure_ascii=False)"],"metadata":{"id":"ap_fvMBsQHJc"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["## Fine-tune model via LLaMA Board"],"metadata":{"id":"2QiXcvdzzW3Y"}},{"cell_type":"code","source":["%cd /content/LLaMA-Factory/\n","!GRADIO_SHARE=1 llamafactory-cli webui"],"metadata":{"id":"YLsdS6V5yUMy"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["## Fine-tune model via Command Line\n","\n","It takes ~30min for training."],"metadata":{"id":"rgR3UFhB0Ifq"}},{"cell_type":"code","source":["import json\n","\n","args = dict(\n"," stage=\"sft\", # do supervised fine-tuning\n"," do_train=True,\n"," model_name_or_path=\"unsloth/llama-3-8b-Instruct-bnb-4bit\", # use bnb-4bit-quantized Llama-3-8B-Instruct model\n"," dataset=\"identity,alpaca_en_demo\", # use alpaca and identity datasets\n"," template=\"llama3\", # use llama3 prompt template\n"," finetuning_type=\"lora\", # use LoRA adapters to save memory\n"," lora_target=\"all\", # attach LoRA adapters to all linear layers\n"," output_dir=\"llama3_lora\", # the path to save LoRA adapters\n"," per_device_train_batch_size=2, # the batch size\n"," gradient_accumulation_steps=4, # the gradient accumulation steps\n"," lr_scheduler_type=\"cosine\", # use cosine learning rate scheduler\n"," logging_steps=10, # log every 10 steps\n"," warmup_ratio=0.1, # use warmup scheduler\n"," save_steps=1000, # save checkpoint every 1000 steps\n"," learning_rate=5e-5, # the learning rate\n"," num_train_epochs=3.0, # the epochs of training\n"," max_samples=500, # use 500 examples in each dataset\n"," max_grad_norm=1.0, # clip gradient norm to 1.0\n"," quantization_bit=4, # use 4-bit QLoRA\n"," loraplus_lr_ratio=16.0, # use LoRA+ algorithm with lambda=16.0\n"," fp16=True, # use float16 mixed precision training\n",")\n","\n","json.dump(args, open(\"train_llama3.json\", \"w\", encoding=\"utf-8\"), indent=2)\n","\n","%cd /content/LLaMA-Factory/\n","\n","!llamafactory-cli train train_llama3.json"],"metadata":{"id":"CS0Qk5OR0i4Q"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["## Infer the fine-tuned model"],"metadata":{"id":"PVNaC-xS5N40"}},{"cell_type":"code","source":["from llamafactory.chat import ChatModel\n","from llamafactory.extras.misc import torch_gc\n","\n","%cd /content/LLaMA-Factory/\n","\n","args = dict(\n"," model_name_or_path=\"unsloth/llama-3-8b-Instruct-bnb-4bit\", # use bnb-4bit-quantized Llama-3-8B-Instruct model\n"," adapter_name_or_path=\"llama3_lora\", # load the saved LoRA adapters\n"," template=\"llama3\", # same to the one in training\n"," finetuning_type=\"lora\", # same to the one in training\n"," quantization_bit=4, # load 4-bit quantized model\n",")\n","chat_model = ChatModel(args)\n","\n","messages = []\n","print(\"Welcome to the CLI application, use `clear` to remove the history, use `exit` to exit the application.\")\n","while True:\n"," query = input(\"\\nUser: \")\n"," if query.strip() == \"exit\":\n"," break\n"," if query.strip() == \"clear\":\n"," messages = []\n"," torch_gc()\n"," print(\"History has been removed.\")\n"," continue\n","\n"," messages.append({\"role\": \"user\", \"content\": query})\n"," print(\"Assistant: \", end=\"\", flush=True)\n","\n"," response = \"\"\n"," for new_text in chat_model.stream_chat(messages):\n"," print(new_text, end=\"\", flush=True)\n"," response += new_text\n"," print()\n"," messages.append({\"role\": \"assistant\", \"content\": response})\n","\n","torch_gc()"],"metadata":{"id":"oh8H9A_25SF9"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["## Merge the LoRA adapter and optionally upload model\n","\n","NOTE: the Colab free version has merely 12GB RAM, where merging LoRA of a 8B model needs at least 18GB RAM, thus you **cannot** perform it in the free version."],"metadata":{"id":"kTESHaFvbNTr"}},{"cell_type":"code","source":["!huggingface-cli login"],"metadata":{"id":"mcNcHcA4bf4Z"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["import json\n","\n","args = dict(\n"," model_name_or_path=\"meta-llama/Meta-Llama-3-8B-Instruct\", # use official non-quantized Llama-3-8B-Instruct model\n"," adapter_name_or_path=\"llama3_lora\", # load the saved LoRA adapters\n"," template=\"llama3\", # same to the one in training\n"," finetuning_type=\"lora\", # same to the one in training\n"," export_dir=\"llama3_lora_merged\", # the path to save the merged model\n"," export_size=2, # the file shard size (in GB) of the merged model\n"," export_device=\"cpu\", # the device used in export, can be chosen from `cpu` and `cuda`\n"," #export_hub_model_id=\"your_id/your_model\", # the Hugging Face hub ID to upload model\n",")\n","\n","json.dump(args, open(\"merge_llama3.json\", \"w\", encoding=\"utf-8\"), indent=2)\n","\n","%cd /content/LLaMA-Factory/\n","\n","!llamafactory-cli export merge_llama3.json"],"metadata":{"id":"IMojogHbaOZF"},"execution_count":null,"outputs":[]}]}
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  jupyter
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  ipywidgets
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  packaging
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- triton
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- xformers
 
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  jupyter
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+ # xformers
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+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:0fd488430f65a2b959d746b81e485a0b596f8e32537979904416dfc021b1181d
3
+ size 179
results/mac-results_lf.csv ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:c5acc087808de5df6839cbf7b170094c6e63445aab4bea15e4be9564b905eb51
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+ size 3236072
scripts/tune-lf.sh ADDED
@@ -0,0 +1,8 @@
 
 
 
 
 
 
 
 
 
1
+ #!/bin/sh
2
+
3
+ BASEDIR=$(dirname "$0")
4
+ cd $BASEDIR/../llama-factory
5
+ echo Current Directory:
6
+ pwd
7
+
8
+ llamafactory-cli train $1