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PrometheanStudio
/
styx-100m

PyTorch
Safetensors
English
talos_gpt
talos
promethean-studios
causal-language-model
from-scratch
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Release Styx-100M trained to 600M tokens

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Files changed (4) hide show
  1. README.md +33 -182
  2. config.json +14 -17
  3. step-293543.pt +3 -0
  4. tokenizer.json +3073 -0
README.md CHANGED
@@ -1,197 +1,48 @@
1
  ---
2
- license: apache-2.0
3
  language:
4
- - en
 
 
5
  tags:
6
- - causal-lm
7
- - language-model
8
- - transformers
9
- - talos
10
- - promethean-studios
11
- - styx
12
- - 100m
13
- pipeline_tag: text-generation
14
  ---
15
 
16
- Styx 100M
17
 
18
- >[!Note]
19
- >Styx 100M is an experimental language model from Promethean Studios and part of the Talos model family.
20
- >
21
- >This release contains the model trained through 100,000 training steps and has 96,482,304 parameters.
22
- >
23
- >Styx is not being presented as a finished or production-ready language model.
24
- >
25
- >It is a research checkpoint and a step in the development of the Talos model family. The goal is to experiment with larger model sizes, training infrastructure, data efficiency, and practical local inference.
26
- >
27
- >Model Details
28
- >
29
- >Property Value
30
- >Parameters 96,482,304
31
- >Vocabulary 1,024
32
- >Hidden size 1,024
33
- >Layers 6
34
- >Attention heads 64
35
- >KV heads 32
36
- >Feed-forward network SwiGLU
37
- >Maximum sequence length 512
38
- >Training steps 100,000
39
- >Architecture Causal Transformer
40
- >
41
- >Styx uses grouped-query attention with 32 KV heads and a SwiGLU feed-forward network.
42
 
43
- >[!Important]
44
- >Styx is a relatively small model by modern language-model standards. Its capabilities should be evaluated accordingly. More parameters do not automatically produce a better model, and this release is primarily useful as a development and research milestone.
45
- >
46
- >What to Expect
47
- >
48
- >Styx has known limitations.
49
- >
50
- >You may encounter:
51
- >
52
- >* Incorrect or fabricated information
53
- >* Repetitive generations
54
- >* Incomplete responses
55
- >* Weak reasoning
56
- >* Inconsistent instruction following
57
- >* Poor generalization
58
- >* Unsafe or undesirable generations
59
- >* Outputs that simply make very little sense
60
- >
61
- >These limitations are intentionally documented rather than hidden.
62
 
63
- >[!Warning]
64
- >Styx is not a production assistant.
65
- >
66
- >It has not been trained or evaluated to provide the reliability, accuracy, instruction following, or safety expected from larger production language models.
67
- >
68
- >The purpose of this release is to make the model and its progress available for experimentation.
69
- >
70
- >Why Release It?
71
- >
72
- >Styx is part of an ongoing development process.
73
- >
74
- >Releasing an imperfect model provides a reference point for evaluating what changes between generations.
75
- >
76
- >This includes experimentation with:
77
- >
78
- >* Model scale
79
- >* Training efficiency
80
- >* Data efficiency
81
- >* Tokenization
82
- >* Attention architectures
83
- >* Training infrastructure
84
- >* Local inference
85
- >* Benchmarking
86
- >* Checkpoint formats
87
- >* Larger future models
88
 
89
- >[!Tip]
90
- >If you’re interested in small language models, Styx can be used as a lightweight model to download, inspect, benchmark, and experiment with locally.
91
- >
92
- >Files
93
- >
94
- >* model.safetensors — model weights in SafeTensors format
95
- >* config.json — model configuration
96
- >* tokenizer/tokenizer.json — Styx tokenizer
97
- >* checkpoints/step-100000.pt — original training checkpoint
98
 
99
- >[!Important]
100
- >model.safetensors contains the model weights for inference.
101
- >
102
- >The original .pt checkpoint contains additional training state and metadata from the training run.
103
- >
104
- >Training
105
- >
106
- >The released model corresponds to:
107
- >
108
- >100,000 training steps
109
- >
110
- >The checkpoint was produced using the Talos training infrastructure developed by Promethean Studios.
111
- >
112
- >Training metadata, including recorded training and validation information, is preserved in the original training checkpoint.
113
- >
114
- >The Talos Model Family
115
- >
116
- >Styx is one stage in a larger model-development effort.
117
- >
118
- >The project began with significantly smaller models and is progressively moving toward larger and more capable architectures.
119
- >
120
- >The purpose of each release is not simply to produce another model checkpoint. It is to learn what works, what doesn’t, and what needs to change before scaling further.
121
 
122
- >[!Note]
123
- >Styx has known problems. That’s expected.
124
- >
125
- >This release is a snapshot of the project at this stage of development, not the final destination.
126
- >
127
- >More Versions Are Coming
128
 
129
- Styx is not the end of the project.
 
 
130
 
131
- Additional models and revisions are planned as development continues. Future releases will incorporate lessons learned from the current generation, including its failures.
 
 
 
132
 
133
- Future development may include:
134
 
135
- * Improved training procedures
136
- * Better data preparation
137
- * Architectural changes
138
- * Improved tokenizer and data pipelines
139
- * More extensive evaluation
140
- * Larger parameter counts
141
- * Better inference support
142
-
143
- >[!Important]
144
- >Future releases may differ substantially from Styx.
145
- >
146
- >Compatibility, architecture, training methods, and model behavior should not be assumed to remain identical between generations.
147
-
148
- Intended Use
149
-
150
- Styx 100M is intended primarily for:
151
-
152
- * Small language-model research
153
- * Local inference experimentation
154
- * Architecture research
155
- * Benchmarking
156
- * Training research
157
- * Data-efficiency experiments
158
- * Educational experimentation
159
- * Development within the Talos ecosystem
160
-
161
- It is particularly suited to people interested in seeing what can be done with relatively small language models.
162
-
163
- Limitations
164
-
165
- Styx has not undergone the level of evaluation associated with large production models.
166
-
167
- Do not rely on its outputs for:
168
-
169
- * Medical decisions
170
- * Legal decisions
171
- * Financial decisions
172
- * Safety-critical systems
173
- * High-stakes automation
174
- * Unsupervised production applications
175
-
176
- >[!Caution]
177
- >Treat model output as untrusted.
178
- >
179
- >Styx can generate incorrect, misleading, or undesirable content. Verify anything important independently.
180
- >
181
- License
182
-
183
- Apache License 2.0.
184
-
185
- Organization
186
-
187
- Promethean Studios
188
-
189
- Styx 100M is released as part of the Talos model family.
190
-
191
- ⸻
192
-
193
- Status
194
-
195
- Experimental • 100M class • 100K training steps • Actively evolving
196
-
197
- Styx is a checkpoint, not the finish line.
 
1
  ---
 
2
  language:
3
+ - en
4
+ license: other
5
+ library_name: pytorch
6
  tags:
7
+ - talos
8
+ - promethean-studios
9
+ - causal-language-model
10
+ - from-scratch
 
 
 
 
11
  ---
12
 
13
+ # Styx-100M
14
 
15
+ Styx is a 96.48-million-parameter language model developed by
16
+ Promethean Studios as part of the Talos model family.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
17
 
18
+ ## Training
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
19
 
20
+ - **Training tokens consumed:** 600,001,892
21
+ - **Final training step:** 293,543
22
+ - **Training loss:** 1.3478
23
+ - **Validation loss:** 1.3707
24
+ - **Vocabulary size:** 1,024
25
+ - **Maximum sequence length:** 512
26
+ - **Tokenizer:** Included as `tokenizer.json`
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
27
 
28
+ ## Files
 
 
 
 
 
 
 
 
29
 
30
+ - `step-293543.pt`: Full PyTorch training checkpoint, including model
31
+ weights and training state.
32
+ - `tokenizer.json`: Matching tokenizer.
33
+ - `config.json`: Architecture and training metadata.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
34
 
35
+ ## Usage and limitations
 
 
 
 
 
36
 
37
+ This is a custom Talos checkpoint, not a drop-in Transformers
38
+ `AutoModelForCausalLM` model. Use the Talos repository's compatible
39
+ model and generation code to load it.
40
 
41
+ Initial generation tests confirm that the checkpoint loads and generates
42
+ text. The sample outputs are not yet consistently coherent, so this
43
+ release should be considered an experimental research checkpoint,
44
+ not a production-ready assistant.
45
 
46
+ ## Project
47
 
48
+ Developed by Promethean Studios.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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