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README.md
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1 |
+
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2 |
+
---
|
3 |
+
|
4 |
+
language:
|
5 |
+
- en
|
6 |
+
license: agpl-3.0
|
7 |
+
tags:
|
8 |
+
- chat
|
9 |
+
base_model:
|
10 |
+
- nvidia/Mistral-NeMo-Minitron-8B-Base
|
11 |
+
datasets:
|
12 |
+
- anthracite-org/kalo-opus-instruct-22k-no-refusal
|
13 |
+
- Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned
|
14 |
+
- lodrick-the-lafted/kalo-opus-instruct-3k-filtered
|
15 |
+
- anthracite-org/nopm_claude_writing_fixed
|
16 |
+
- Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned
|
17 |
+
- anthracite-org/kalo_opus_misc_240827
|
18 |
+
- anthracite-org/kalo_misc_part2
|
19 |
+
License: agpl-3.0
|
20 |
+
Language:
|
21 |
+
- En
|
22 |
+
Pipeline_tag: text-generation
|
23 |
+
Base_model: nvidia/Mistral-NeMo-Minitron-8B-Base
|
24 |
+
Tags:
|
25 |
+
- Chat
|
26 |
+
model-index:
|
27 |
+
- name: Tor-8B
|
28 |
+
results:
|
29 |
+
- task:
|
30 |
+
type: text-generation
|
31 |
+
name: Text Generation
|
32 |
+
dataset:
|
33 |
+
name: IFEval (0-Shot)
|
34 |
+
type: HuggingFaceH4/ifeval
|
35 |
+
args:
|
36 |
+
num_few_shot: 0
|
37 |
+
metrics:
|
38 |
+
- type: inst_level_strict_acc and prompt_level_strict_acc
|
39 |
+
value: 23.82
|
40 |
+
name: strict accuracy
|
41 |
+
source:
|
42 |
+
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Delta-Vector/Tor-8B
|
43 |
+
name: Open LLM Leaderboard
|
44 |
+
- task:
|
45 |
+
type: text-generation
|
46 |
+
name: Text Generation
|
47 |
+
dataset:
|
48 |
+
name: BBH (3-Shot)
|
49 |
+
type: BBH
|
50 |
+
args:
|
51 |
+
num_few_shot: 3
|
52 |
+
metrics:
|
53 |
+
- type: acc_norm
|
54 |
+
value: 31.74
|
55 |
+
name: normalized accuracy
|
56 |
+
source:
|
57 |
+
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Delta-Vector/Tor-8B
|
58 |
+
name: Open LLM Leaderboard
|
59 |
+
- task:
|
60 |
+
type: text-generation
|
61 |
+
name: Text Generation
|
62 |
+
dataset:
|
63 |
+
name: MATH Lvl 5 (4-Shot)
|
64 |
+
type: hendrycks/competition_math
|
65 |
+
args:
|
66 |
+
num_few_shot: 4
|
67 |
+
metrics:
|
68 |
+
- type: exact_match
|
69 |
+
value: 5.44
|
70 |
+
name: exact match
|
71 |
+
source:
|
72 |
+
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Delta-Vector/Tor-8B
|
73 |
+
name: Open LLM Leaderboard
|
74 |
+
- task:
|
75 |
+
type: text-generation
|
76 |
+
name: Text Generation
|
77 |
+
dataset:
|
78 |
+
name: GPQA (0-shot)
|
79 |
+
type: Idavidrein/gpqa
|
80 |
+
args:
|
81 |
+
num_few_shot: 0
|
82 |
+
metrics:
|
83 |
+
- type: acc_norm
|
84 |
+
value: 9.84
|
85 |
+
name: acc_norm
|
86 |
+
source:
|
87 |
+
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Delta-Vector/Tor-8B
|
88 |
+
name: Open LLM Leaderboard
|
89 |
+
- task:
|
90 |
+
type: text-generation
|
91 |
+
name: Text Generation
|
92 |
+
dataset:
|
93 |
+
name: MuSR (0-shot)
|
94 |
+
type: TAUR-Lab/MuSR
|
95 |
+
args:
|
96 |
+
num_few_shot: 0
|
97 |
+
metrics:
|
98 |
+
- type: acc_norm
|
99 |
+
value: 8.82
|
100 |
+
name: acc_norm
|
101 |
+
source:
|
102 |
+
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Delta-Vector/Tor-8B
|
103 |
+
name: Open LLM Leaderboard
|
104 |
+
- task:
|
105 |
+
type: text-generation
|
106 |
+
name: Text Generation
|
107 |
+
dataset:
|
108 |
+
name: MMLU-PRO (5-shot)
|
109 |
+
type: TIGER-Lab/MMLU-Pro
|
110 |
+
config: main
|
111 |
+
split: test
|
112 |
+
args:
|
113 |
+
num_few_shot: 5
|
114 |
+
metrics:
|
115 |
+
- type: acc
|
116 |
+
value: 30.33
|
117 |
+
name: accuracy
|
118 |
+
source:
|
119 |
+
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Delta-Vector/Tor-8B
|
120 |
+
name: Open LLM Leaderboard
|
121 |
+
|
122 |
+
---
|
123 |
+
|
124 |
+
[![QuantFactory Banner](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)](https://hf.co/QuantFactory)
|
125 |
+
|
126 |
+
|
127 |
+
# QuantFactory/Tor-8B-GGUF
|
128 |
+
This is quantized version of [Delta-Vector/Tor-8B](https://huggingface.co/Delta-Vector/Tor-8B) created using llama.cpp
|
129 |
+
|
130 |
+
# Original Model Card
|
131 |
+
|
132 |
+
|
133 |
+
![](https://huggingface.co/Delta-Vector/Tor-8B/resolve/main/FinalTor8B.jpg)
|
134 |
+
|
135 |
+
|
136 |
+
|
137 |
+
An earlier checkpoint of [Darkens-8B](https://huggingface.co/Delta-Vector/Darkens-8B) using the same configuration that i felt was different enough from it's 4 epoch cousin to release, Finetuned ontop of the Prune/Distill NeMo 8B done by Nvidia, This model aims to have generally good prose and writing while not falling into claude-isms.
|
138 |
+
|
139 |
+
|
140 |
+
# Quants
|
141 |
+
|
142 |
+
GGUF: https://huggingface.co/Delta-Vector/Tor-8B-GGUF
|
143 |
+
|
144 |
+
EXL2: https://huggingface.co/Delta-Vector/Tor-8B-EXL2
|
145 |
+
|
146 |
+
|
147 |
+
## Prompting
|
148 |
+
Model has been Instruct tuned with the ChatML formatting. A typical input would look like this:
|
149 |
+
|
150 |
+
```py
|
151 |
+
"""<|im_start|>system
|
152 |
+
system prompt<|im_end|>
|
153 |
+
<|im_start|>user
|
154 |
+
Hi there!<|im_end|>
|
155 |
+
<|im_start|>assistant
|
156 |
+
Nice to meet you!<|im_end|>
|
157 |
+
<|im_start|>user
|
158 |
+
Can I ask a question?<|im_end|>
|
159 |
+
<|im_start|>assistant
|
160 |
+
"""
|
161 |
+
```
|
162 |
+
## System Prompting
|
163 |
+
|
164 |
+
I would highly recommend using Sao10k's Euryale System prompt, But the "Roleplay Simple" system prompt provided within SillyTavern will work aswell.
|
165 |
+
|
166 |
+
```
|
167 |
+
Currently, your role is {{char}}, described in detail below. As {{char}}, continue the narrative exchange with {{user}}.
|
168 |
+
|
169 |
+
<Guidelines>
|
170 |
+
• Maintain the character persona but allow it to evolve with the story.
|
171 |
+
• Be creative and proactive. Drive the story forward, introducing plotlines and events when relevant.
|
172 |
+
• All types of outputs are encouraged; respond accordingly to the narrative.
|
173 |
+
• Include dialogues, actions, and thoughts in each response.
|
174 |
+
• Utilize all five senses to describe scenarios within {{char}}'s dialogue.
|
175 |
+
• Use emotional symbols such as "!" and "~" in appropriate contexts.
|
176 |
+
• Incorporate onomatopoeia when suitable.
|
177 |
+
• Allow time for {{user}} to respond with their own input, respecting their agency.
|
178 |
+
• Act as secondary characters and NPCs as needed, and remove them when appropriate.
|
179 |
+
• When prompted for an Out of Character [OOC:] reply, answer neutrally and in plaintext, not as {{char}}.
|
180 |
+
</Guidelines>
|
181 |
+
|
182 |
+
<Forbidden>
|
183 |
+
• Using excessive literary embellishments and purple prose unless dictated by {{char}}'s persona.
|
184 |
+
• Writing for, speaking, thinking, acting, or replying as {{user}} in your response.
|
185 |
+
• Repetitive and monotonous outputs.
|
186 |
+
• Positivity bias in your replies.
|
187 |
+
• Being overly extreme or NSFW when the narrative context is inappropriate.
|
188 |
+
</Forbidden>
|
189 |
+
|
190 |
+
Follow the instructions in <Guidelines></Guidelines>, avoiding the items listed in <Forbidden></Forbidden>.
|
191 |
+
|
192 |
+
```
|
193 |
+
|
194 |
+
|
195 |
+
## Axolotl config
|
196 |
+
|
197 |
+
<details><summary>See axolotl config</summary>
|
198 |
+
|
199 |
+
Axolotl version: `0.4.1`
|
200 |
+
```yaml
|
201 |
+
base_model: Dans-DiscountModels/Mistral-NeMo-Minitron-8B-Base-ChatML
|
202 |
+
model_type: AutoModelForCausalLM
|
203 |
+
tokenizer_type: AutoTokenizer
|
204 |
+
|
205 |
+
plugins:
|
206 |
+
- axolotl.integrations.liger.LigerPlugin
|
207 |
+
liger_rope: true
|
208 |
+
liger_rms_norm: true
|
209 |
+
liger_swiglu: true
|
210 |
+
#liger_cross_entropy: true
|
211 |
+
liger_fused_linear_cross_entropy: true
|
212 |
+
|
213 |
+
load_in_8bit: false
|
214 |
+
load_in_4bit: false
|
215 |
+
strict: false
|
216 |
+
|
217 |
+
datasets:
|
218 |
+
- path: PRIVATE CLAUDE LOG FILTER
|
219 |
+
type: sharegpt
|
220 |
+
conversation: chatml
|
221 |
+
- path: anthracite-org/kalo-opus-instruct-22k-no-refusal
|
222 |
+
type: sharegpt
|
223 |
+
conversation: chatml
|
224 |
+
- path: Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned
|
225 |
+
type: sharegpt
|
226 |
+
conversation: chatml
|
227 |
+
- path: lodrick-the-lafted/kalo-opus-instruct-3k-filtered
|
228 |
+
type: sharegpt
|
229 |
+
conversation: chatml
|
230 |
+
- path: anthracite-org/nopm_claude_writing_fixed
|
231 |
+
type: sharegpt
|
232 |
+
conversation: chatml
|
233 |
+
- path: Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned
|
234 |
+
type: sharegpt
|
235 |
+
conversation: chatml
|
236 |
+
- path: anthracite-org/kalo_opus_misc_240827
|
237 |
+
type: sharegpt
|
238 |
+
conversation: chatml
|
239 |
+
- path: anthracite-org/kalo_misc_part2
|
240 |
+
type: sharegpt
|
241 |
+
conversation: chatml
|
242 |
+
chat_template: chatml
|
243 |
+
shuffle_merged_datasets: false
|
244 |
+
default_system_message: "You are a helpful assistant that responds to the user."
|
245 |
+
dataset_prepared_path: /workspace/data/8b-nemo-fft-data
|
246 |
+
val_set_size: 0.0
|
247 |
+
output_dir: /workspace/data/8b-nemo-fft-out
|
248 |
+
|
249 |
+
sequence_len: 16384
|
250 |
+
sample_packing: true
|
251 |
+
eval_sample_packing: false
|
252 |
+
pad_to_sequence_len: true
|
253 |
+
|
254 |
+
adapter:
|
255 |
+
lora_model_dir:
|
256 |
+
lora_r:
|
257 |
+
lora_alpha:
|
258 |
+
lora_dropout:
|
259 |
+
lora_target_linear:
|
260 |
+
lora_fan_in_fan_out:
|
261 |
+
|
262 |
+
wandb_project: 8b-nemoprune-fft
|
263 |
+
wandb_entity:
|
264 |
+
wandb_watch:
|
265 |
+
wandb_name: attempt-01
|
266 |
+
wandb_log_model:
|
267 |
+
|
268 |
+
gradient_accumulation_steps: 2
|
269 |
+
micro_batch_size: 2
|
270 |
+
num_epochs: 4
|
271 |
+
optimizer: adamw_bnb_8bit
|
272 |
+
lr_scheduler: cosine
|
273 |
+
learning_rate: 0.00001
|
274 |
+
|
275 |
+
train_on_inputs: false
|
276 |
+
group_by_length: false
|
277 |
+
bf16: auto
|
278 |
+
fp16:
|
279 |
+
tf32: false
|
280 |
+
|
281 |
+
gradient_checkpointing: true
|
282 |
+
early_stopping_patience:
|
283 |
+
resume_from_checkpoint: /workspace/workspace/thing
|
284 |
+
local_rank:
|
285 |
+
logging_steps: 1
|
286 |
+
xformers_attention:
|
287 |
+
flash_attention: true
|
288 |
+
|
289 |
+
warmup_steps: 10
|
290 |
+
evals_per_epoch:
|
291 |
+
eval_table_size:
|
292 |
+
eval_max_new_tokens:
|
293 |
+
saves_per_epoch: 1
|
294 |
+
debug:
|
295 |
+
deepspeed: deepspeed_configs/zero3_bf16.json
|
296 |
+
weight_decay: 0.001
|
297 |
+
fsdp:
|
298 |
+
fsdp_config:
|
299 |
+
special_tokens:
|
300 |
+
pad_token: <pad>
|
301 |
+
|
302 |
+
|
303 |
+
```
|
304 |
+
|
305 |
+
</details><br>
|
306 |
+
|
307 |
+
## Credits
|
308 |
+
|
309 |
+
Thank you to [Lucy Knada](https://huggingface.co/lucyknada), [Kalomaze](https://huggingface.co/kalomaze), [Kubernetes Bad](https://huggingface.co/kubernetes-bad) and the rest of [Anthracite](https://huggingface.co/anthracite-org) (But not Alpin.)
|
310 |
+
|
311 |
+
|
312 |
+
## Training
|
313 |
+
The training was done for 4 epochs. (This model is the 2 epoch checkpoint), I used 10 x [A40s](https://www.nvidia.com/en-us/data-center/a40/) GPUs graciously provided by [Kalomaze](https://huggingface.co/kalomaze) for the full-parameter fine-tuning of the model.
|
314 |
+
|
315 |
+
[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
|
316 |
+
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
|
317 |
+
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Delta-Vector__Tor-8B)
|
318 |
+
|
319 |
+
| Metric |Value|
|
320 |
+
|-------------------|----:|
|
321 |
+
|Avg. |18.33|
|
322 |
+
|IFEval (0-Shot) |23.82|
|
323 |
+
|BBH (3-Shot) |31.74|
|
324 |
+
|MATH Lvl 5 (4-Shot)| 5.44|
|
325 |
+
|GPQA (0-shot) | 9.84|
|
326 |
+
|MuSR (0-shot) | 8.82|
|
327 |
+
|MMLU-PRO (5-shot) |30.33|
|
328 |
+
|
329 |
+
|