ronantakizawa commited on
Commit
7298b2b
·
verified ·
1 Parent(s): 64b7705

Upload GPTQ-quantized SmolVLM-Instruct (4-bit)

Browse files
Files changed (4) hide show
  1. README.md +199 -0
  2. config.json +355 -0
  3. generation_config.json +7 -0
  4. model.safetensors +3 -0
README.md ADDED
@@ -0,0 +1,199 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: transformers
3
+ tags: []
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+ This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
config.json ADDED
@@ -0,0 +1,355 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "architectures": [
3
+ "Idefics3ForConditionalGeneration"
4
+ ],
5
+ "dtype": "bfloat16",
6
+ "image_seq_len": 81,
7
+ "image_token_id": 49153,
8
+ "model_type": "idefics3",
9
+ "pad_token_id": 128002,
10
+ "quantization_config": {
11
+ "config_groups": {
12
+ "group_0": {
13
+ "format": "pack-quantized",
14
+ "input_activations": null,
15
+ "output_activations": null,
16
+ "targets": [
17
+ "Linear"
18
+ ],
19
+ "weights": {
20
+ "actorder": "static",
21
+ "block_structure": null,
22
+ "dynamic": false,
23
+ "group_size": 128,
24
+ "num_bits": 4,
25
+ "observer": "minmax",
26
+ "observer_kwargs": {},
27
+ "strategy": "group",
28
+ "symmetric": true,
29
+ "type": "int"
30
+ }
31
+ }
32
+ },
33
+ "format": "pack-quantized",
34
+ "global_compression_ratio": null,
35
+ "ignore": [
36
+ "model.vision_model.encoder.layers.0.self_attn.k_proj",
37
+ "model.vision_model.encoder.layers.0.self_attn.v_proj",
38
+ "model.vision_model.encoder.layers.0.self_attn.q_proj",
39
+ "model.vision_model.encoder.layers.0.self_attn.out_proj",
40
+ "model.vision_model.encoder.layers.0.mlp.fc1",
41
+ "model.vision_model.encoder.layers.0.mlp.fc2",
42
+ "model.vision_model.encoder.layers.1.self_attn.k_proj",
43
+ "model.vision_model.encoder.layers.1.self_attn.v_proj",
44
+ "model.vision_model.encoder.layers.1.self_attn.q_proj",
45
+ "model.vision_model.encoder.layers.1.self_attn.out_proj",
46
+ "model.vision_model.encoder.layers.1.mlp.fc1",
47
+ "model.vision_model.encoder.layers.1.mlp.fc2",
48
+ "model.vision_model.encoder.layers.2.self_attn.k_proj",
49
+ "model.vision_model.encoder.layers.2.self_attn.v_proj",
50
+ "model.vision_model.encoder.layers.2.self_attn.q_proj",
51
+ "model.vision_model.encoder.layers.2.self_attn.out_proj",
52
+ "model.vision_model.encoder.layers.2.mlp.fc1",
53
+ "model.vision_model.encoder.layers.2.mlp.fc2",
54
+ "model.vision_model.encoder.layers.3.self_attn.k_proj",
55
+ "model.vision_model.encoder.layers.3.self_attn.v_proj",
56
+ "model.vision_model.encoder.layers.3.self_attn.q_proj",
57
+ "model.vision_model.encoder.layers.3.self_attn.out_proj",
58
+ "model.vision_model.encoder.layers.3.mlp.fc1",
59
+ "model.vision_model.encoder.layers.3.mlp.fc2",
60
+ "model.vision_model.encoder.layers.4.self_attn.k_proj",
61
+ "model.vision_model.encoder.layers.4.self_attn.v_proj",
62
+ "model.vision_model.encoder.layers.4.self_attn.q_proj",
63
+ "model.vision_model.encoder.layers.4.self_attn.out_proj",
64
+ "model.vision_model.encoder.layers.4.mlp.fc1",
65
+ "model.vision_model.encoder.layers.4.mlp.fc2",
66
+ "model.vision_model.encoder.layers.5.self_attn.k_proj",
67
+ "model.vision_model.encoder.layers.5.self_attn.v_proj",
68
+ "model.vision_model.encoder.layers.5.self_attn.q_proj",
69
+ "model.vision_model.encoder.layers.5.self_attn.out_proj",
70
+ "model.vision_model.encoder.layers.5.mlp.fc1",
71
+ "model.vision_model.encoder.layers.5.mlp.fc2",
72
+ "model.vision_model.encoder.layers.6.self_attn.k_proj",
73
+ "model.vision_model.encoder.layers.6.self_attn.v_proj",
74
+ "model.vision_model.encoder.layers.6.self_attn.q_proj",
75
+ "model.vision_model.encoder.layers.6.self_attn.out_proj",
76
+ "model.vision_model.encoder.layers.6.mlp.fc1",
77
+ "model.vision_model.encoder.layers.6.mlp.fc2",
78
+ "model.vision_model.encoder.layers.7.self_attn.k_proj",
79
+ "model.vision_model.encoder.layers.7.self_attn.v_proj",
80
+ "model.vision_model.encoder.layers.7.self_attn.q_proj",
81
+ "model.vision_model.encoder.layers.7.self_attn.out_proj",
82
+ "model.vision_model.encoder.layers.7.mlp.fc1",
83
+ "model.vision_model.encoder.layers.7.mlp.fc2",
84
+ "model.vision_model.encoder.layers.8.self_attn.k_proj",
85
+ "model.vision_model.encoder.layers.8.self_attn.v_proj",
86
+ "model.vision_model.encoder.layers.8.self_attn.q_proj",
87
+ "model.vision_model.encoder.layers.8.self_attn.out_proj",
88
+ "model.vision_model.encoder.layers.8.mlp.fc1",
89
+ "model.vision_model.encoder.layers.8.mlp.fc2",
90
+ "model.vision_model.encoder.layers.9.self_attn.k_proj",
91
+ "model.vision_model.encoder.layers.9.self_attn.v_proj",
92
+ "model.vision_model.encoder.layers.9.self_attn.q_proj",
93
+ "model.vision_model.encoder.layers.9.self_attn.out_proj",
94
+ "model.vision_model.encoder.layers.9.mlp.fc1",
95
+ "model.vision_model.encoder.layers.9.mlp.fc2",
96
+ "model.vision_model.encoder.layers.10.self_attn.k_proj",
97
+ "model.vision_model.encoder.layers.10.self_attn.v_proj",
98
+ "model.vision_model.encoder.layers.10.self_attn.q_proj",
99
+ "model.vision_model.encoder.layers.10.self_attn.out_proj",
100
+ "model.vision_model.encoder.layers.10.mlp.fc1",
101
+ "model.vision_model.encoder.layers.10.mlp.fc2",
102
+ "model.vision_model.encoder.layers.11.self_attn.k_proj",
103
+ "model.vision_model.encoder.layers.11.self_attn.v_proj",
104
+ "model.vision_model.encoder.layers.11.self_attn.q_proj",
105
+ "model.vision_model.encoder.layers.11.self_attn.out_proj",
106
+ "model.vision_model.encoder.layers.11.mlp.fc1",
107
+ "model.vision_model.encoder.layers.11.mlp.fc2",
108
+ "model.vision_model.encoder.layers.12.self_attn.k_proj",
109
+ "model.vision_model.encoder.layers.12.self_attn.v_proj",
110
+ "model.vision_model.encoder.layers.12.self_attn.q_proj",
111
+ "model.vision_model.encoder.layers.12.self_attn.out_proj",
112
+ "model.vision_model.encoder.layers.12.mlp.fc1",
113
+ "model.vision_model.encoder.layers.12.mlp.fc2",
114
+ "model.vision_model.encoder.layers.13.self_attn.k_proj",
115
+ "model.vision_model.encoder.layers.13.self_attn.v_proj",
116
+ "model.vision_model.encoder.layers.13.self_attn.q_proj",
117
+ "model.vision_model.encoder.layers.13.self_attn.out_proj",
118
+ "model.vision_model.encoder.layers.13.mlp.fc1",
119
+ "model.vision_model.encoder.layers.13.mlp.fc2",
120
+ "model.vision_model.encoder.layers.14.self_attn.k_proj",
121
+ "model.vision_model.encoder.layers.14.self_attn.v_proj",
122
+ "model.vision_model.encoder.layers.14.self_attn.q_proj",
123
+ "model.vision_model.encoder.layers.14.self_attn.out_proj",
124
+ "model.vision_model.encoder.layers.14.mlp.fc1",
125
+ "model.vision_model.encoder.layers.14.mlp.fc2",
126
+ "model.vision_model.encoder.layers.15.self_attn.k_proj",
127
+ "model.vision_model.encoder.layers.15.self_attn.v_proj",
128
+ "model.vision_model.encoder.layers.15.self_attn.q_proj",
129
+ "model.vision_model.encoder.layers.15.self_attn.out_proj",
130
+ "model.vision_model.encoder.layers.15.mlp.fc1",
131
+ "model.vision_model.encoder.layers.15.mlp.fc2",
132
+ "model.vision_model.encoder.layers.16.self_attn.k_proj",
133
+ "model.vision_model.encoder.layers.16.self_attn.v_proj",
134
+ "model.vision_model.encoder.layers.16.self_attn.q_proj",
135
+ "model.vision_model.encoder.layers.16.self_attn.out_proj",
136
+ "model.vision_model.encoder.layers.16.mlp.fc1",
137
+ "model.vision_model.encoder.layers.16.mlp.fc2",
138
+ "model.vision_model.encoder.layers.17.self_attn.k_proj",
139
+ "model.vision_model.encoder.layers.17.self_attn.v_proj",
140
+ "model.vision_model.encoder.layers.17.self_attn.q_proj",
141
+ "model.vision_model.encoder.layers.17.self_attn.out_proj",
142
+ "model.vision_model.encoder.layers.17.mlp.fc1",
143
+ "model.vision_model.encoder.layers.17.mlp.fc2",
144
+ "model.vision_model.encoder.layers.18.self_attn.k_proj",
145
+ "model.vision_model.encoder.layers.18.self_attn.v_proj",
146
+ "model.vision_model.encoder.layers.18.self_attn.q_proj",
147
+ "model.vision_model.encoder.layers.18.self_attn.out_proj",
148
+ "model.vision_model.encoder.layers.18.mlp.fc1",
149
+ "model.vision_model.encoder.layers.18.mlp.fc2",
150
+ "model.vision_model.encoder.layers.19.self_attn.k_proj",
151
+ "model.vision_model.encoder.layers.19.self_attn.v_proj",
152
+ "model.vision_model.encoder.layers.19.self_attn.q_proj",
153
+ "model.vision_model.encoder.layers.19.self_attn.out_proj",
154
+ "model.vision_model.encoder.layers.19.mlp.fc1",
155
+ "model.vision_model.encoder.layers.19.mlp.fc2",
156
+ "model.vision_model.encoder.layers.20.self_attn.k_proj",
157
+ "model.vision_model.encoder.layers.20.self_attn.v_proj",
158
+ "model.vision_model.encoder.layers.20.self_attn.q_proj",
159
+ "model.vision_model.encoder.layers.20.self_attn.out_proj",
160
+ "model.vision_model.encoder.layers.20.mlp.fc1",
161
+ "model.vision_model.encoder.layers.20.mlp.fc2",
162
+ "model.vision_model.encoder.layers.21.self_attn.k_proj",
163
+ "model.vision_model.encoder.layers.21.self_attn.v_proj",
164
+ "model.vision_model.encoder.layers.21.self_attn.q_proj",
165
+ "model.vision_model.encoder.layers.21.self_attn.out_proj",
166
+ "model.vision_model.encoder.layers.21.mlp.fc1",
167
+ "model.vision_model.encoder.layers.21.mlp.fc2",
168
+ "model.vision_model.encoder.layers.22.self_attn.k_proj",
169
+ "model.vision_model.encoder.layers.22.self_attn.v_proj",
170
+ "model.vision_model.encoder.layers.22.self_attn.q_proj",
171
+ "model.vision_model.encoder.layers.22.self_attn.out_proj",
172
+ "model.vision_model.encoder.layers.22.mlp.fc1",
173
+ "model.vision_model.encoder.layers.22.mlp.fc2",
174
+ "model.vision_model.encoder.layers.23.self_attn.k_proj",
175
+ "model.vision_model.encoder.layers.23.self_attn.v_proj",
176
+ "model.vision_model.encoder.layers.23.self_attn.q_proj",
177
+ "model.vision_model.encoder.layers.23.self_attn.out_proj",
178
+ "model.vision_model.encoder.layers.23.mlp.fc1",
179
+ "model.vision_model.encoder.layers.23.mlp.fc2",
180
+ "model.vision_model.encoder.layers.24.self_attn.k_proj",
181
+ "model.vision_model.encoder.layers.24.self_attn.v_proj",
182
+ "model.vision_model.encoder.layers.24.self_attn.q_proj",
183
+ "model.vision_model.encoder.layers.24.self_attn.out_proj",
184
+ "model.vision_model.encoder.layers.24.mlp.fc1",
185
+ "model.vision_model.encoder.layers.24.mlp.fc2",
186
+ "model.vision_model.encoder.layers.25.self_attn.k_proj",
187
+ "model.vision_model.encoder.layers.25.self_attn.v_proj",
188
+ "model.vision_model.encoder.layers.25.self_attn.q_proj",
189
+ "model.vision_model.encoder.layers.25.self_attn.out_proj",
190
+ "model.vision_model.encoder.layers.25.mlp.fc1",
191
+ "model.vision_model.encoder.layers.25.mlp.fc2",
192
+ "model.vision_model.encoder.layers.26.self_attn.k_proj",
193
+ "model.vision_model.encoder.layers.26.self_attn.v_proj",
194
+ "model.vision_model.encoder.layers.26.self_attn.q_proj",
195
+ "model.vision_model.encoder.layers.26.self_attn.out_proj",
196
+ "model.vision_model.encoder.layers.26.mlp.fc1",
197
+ "model.vision_model.encoder.layers.26.mlp.fc2",
198
+ "model.connector.modality_projection.proj",
199
+ "lm_head"
200
+ ],
201
+ "kv_cache_scheme": null,
202
+ "quant_method": "compressed-tensors",
203
+ "quantization_status": "compressed",
204
+ "sparsity_config": {}
205
+ },
206
+ "scale_factor": 3,
207
+ "text_config": {
208
+ "_attn_implementation_autoset": false,
209
+ "_flash_attn_2_enabled": true,
210
+ "_name_or_path": "/fsx/m4/experiments/local_experiment_dir/s3_async_temporary_checkpoint_folder/tr_324_opt_400/unwrapped_model",
211
+ "architectures": [
212
+ "VLlama3ForCausalLM"
213
+ ],
214
+ "attention_bias": false,
215
+ "attention_dropout": 0.0,
216
+ "bos_token_id": 0,
217
+ "dtype": "bfloat16",
218
+ "eos_token_id": 0,
219
+ "head_dim": 64,
220
+ "hidden_act": "silu",
221
+ "hidden_size": 2048,
222
+ "initializer_range": 0.02,
223
+ "intermediate_size": 8192,
224
+ "max_position_embeddings": 16384,
225
+ "mlp_bias": false,
226
+ "model_type": "llama",
227
+ "neftune_noise_alpha": 0.0,
228
+ "num_attention_heads": 32,
229
+ "num_hidden_layers": 24,
230
+ "num_key_value_heads": 32,
231
+ "pad_token_id": 2,
232
+ "perceiver_config": {
233
+ "_attn_implementation_autoset": false,
234
+ "_name_or_path": "",
235
+ "add_cross_attention": false,
236
+ "architectures": null,
237
+ "attention_dropout": 0.0,
238
+ "bad_words_ids": null,
239
+ "begin_suppress_tokens": null,
240
+ "bos_token_id": null,
241
+ "chunk_size_feed_forward": 0,
242
+ "cross_attention_hidden_size": null,
243
+ "decoder_start_token_id": null,
244
+ "diversity_penalty": 0.0,
245
+ "do_sample": false,
246
+ "early_stopping": false,
247
+ "encoder_no_repeat_ngram_size": 0,
248
+ "eos_token_id": null,
249
+ "exponential_decay_length_penalty": null,
250
+ "finetuning_task": null,
251
+ "forced_bos_token_id": null,
252
+ "forced_eos_token_id": null,
253
+ "hidden_act": "silu",
254
+ "id2label": {
255
+ "0": "LABEL_0",
256
+ "1": "LABEL_1"
257
+ },
258
+ "is_decoder": false,
259
+ "is_encoder_decoder": false,
260
+ "label2id": {
261
+ "LABEL_0": 0,
262
+ "LABEL_1": 1
263
+ },
264
+ "length_penalty": 1.0,
265
+ "max_length": 20,
266
+ "min_length": 0,
267
+ "model_type": "vllama3",
268
+ "no_repeat_ngram_size": 0,
269
+ "num_beam_groups": 1,
270
+ "num_beams": 1,
271
+ "num_key_value_heads": 1,
272
+ "num_return_sequences": 1,
273
+ "output_attentions": false,
274
+ "output_hidden_states": false,
275
+ "output_scores": false,
276
+ "pad_token_id": null,
277
+ "prefix": null,
278
+ "problem_type": null,
279
+ "pruned_heads": {},
280
+ "qk_layer_norms_perceiver": false,
281
+ "remove_invalid_values": false,
282
+ "repetition_penalty": 1.0,
283
+ "resampler_depth": 6,
284
+ "resampler_head_dim": 96,
285
+ "resampler_n_heads": 16,
286
+ "resampler_n_latents": 64,
287
+ "return_dict": true,
288
+ "return_dict_in_generate": false,
289
+ "sep_token_id": null,
290
+ "suppress_tokens": null,
291
+ "task_specific_params": null,
292
+ "temperature": 1.0,
293
+ "tf_legacy_loss": false,
294
+ "tie_encoder_decoder": false,
295
+ "tie_word_embeddings": true,
296
+ "tokenizer_class": null,
297
+ "top_k": 50,
298
+ "top_p": 1.0,
299
+ "torch_dtype": null,
300
+ "torchscript": false,
301
+ "transformers_version": "4.46.0",
302
+ "typical_p": 1.0,
303
+ "use_bfloat16": false
304
+ },
305
+ "pretraining_tp": 1,
306
+ "qk_layer_norms": false,
307
+ "rms_norm_eps": 1e-05,
308
+ "rope_scaling": null,
309
+ "rope_theta": 273768.0,
310
+ "use_cache": true,
311
+ "use_resampler": false,
312
+ "vocab_size": 49155
313
+ },
314
+ "tie_word_embeddings": false,
315
+ "transformers.js_config": {
316
+ "dtype": {
317
+ "decoder_model_merged": "q4",
318
+ "embed_tokens": "auto",
319
+ "vision_encoder": "auto"
320
+ },
321
+ "kv_cache_dtype": {
322
+ "fp16": "float16",
323
+ "q4f16": "float16"
324
+ },
325
+ "use_external_data_format": {
326
+ "decoder_model_merged.onnx": true,
327
+ "decoder_model_merged_fp16.onnx": true
328
+ }
329
+ },
330
+ "transformers_version": "4.57.0",
331
+ "use_cache": true,
332
+ "vision_config": {
333
+ "_attn_implementation_autoset": false,
334
+ "attention_dropout": 0.0,
335
+ "hidden_act": "gelu_pytorch_tanh",
336
+ "hidden_size": 1152,
337
+ "image_size": 384,
338
+ "initializer_range": 0.02,
339
+ "intermediate_size": 4304,
340
+ "layer_norm_eps": 1e-06,
341
+ "max_image_size": {
342
+ "longest_edge": 384
343
+ },
344
+ "model_type": "idefics3_vision",
345
+ "num_attention_heads": 16,
346
+ "num_channels": 3,
347
+ "num_hidden_layers": 27,
348
+ "patch_size": 14,
349
+ "size": {
350
+ "longest_edge": 1920
351
+ },
352
+ "tie_word_embeddings": false
353
+ },
354
+ "vocab_size": 49155
355
+ }
generation_config.json ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ {
2
+ "_from_model_config": true,
3
+ "bos_token_id": 0,
4
+ "eos_token_id": 49154,
5
+ "pad_token_id": 2,
6
+ "transformers_version": "4.57.0"
7
+ }
model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:4c839593ef0414471848487b6f2bf99a2a994cce5c6cdc41f6f934f98cd64d99
3
+ size 2101921576