Add files using upload-large-folder tool
Browse files- README.md +88 -0
- config.json +1284 -0
- generation_config.json +12 -0
- model.safetensors +3 -0
- smash_config.json +39 -0
README.md
ADDED
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@@ -0,0 +1,88 @@
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| 1 |
+
---
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| 2 |
+
library_name: transformers
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| 3 |
+
tags:
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| 4 |
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- safetensors
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| 5 |
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- pruna_pro-ai
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| 6 |
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- pruna-ai
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| 7 |
+
---
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| 8 |
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| 9 |
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# Model Card for loulou2/tiny_llama_higgs
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| 10 |
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This model was created using the [pruna](https://github.com/PrunaAI/pruna) library. Pruna is a model optimization framework built for developers, enabling you to deliver more efficient models with minimal implementation overhead.
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| 12 |
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| 13 |
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## Usage
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| 14 |
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| 15 |
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First things first, you need to install the pruna library:
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| 17 |
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```bash
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| 18 |
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pip install pruna_pro
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| 19 |
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```
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| 20 |
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| 21 |
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You can [use the transformers library to load the model](https://huggingface.co/loulou2/tiny_llama_higgs?library=transformers) but this might not include all optimizations by default.
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| 23 |
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To ensure that all optimizations are applied, use the pruna library to load the model using the following code:
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```python
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from pruna_pro import PrunaProModel
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loaded_model = PrunaProModel.from_pretrained(
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"loulou2/tiny_llama_higgs"
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)
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# we can then run inference using the methods supported by the base model
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```
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Alternatively, you can visit [the Pruna documentation](https://docs.pruna.ai/en/stable/) for more information.
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## Smash Configuration
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The compression configuration of the model is stored in the `smash_config.json` file, which describes the optimization methods that were applied to the model.
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```bash
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| 41 |
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{
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"batcher": null,
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| 43 |
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"cacher": null,
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| 44 |
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"compiler": null,
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| 45 |
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"distiller": null,
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| 46 |
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"distributer": null,
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| 47 |
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"enhancer": null,
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"factorizer": null,
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"kernel": null,
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| 50 |
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"pruner": null,
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"quantizer": "higgs",
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"recoverer": null,
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| 53 |
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"higgs_group_size": 256,
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| 54 |
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"higgs_hadamard_size": 1024,
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| 55 |
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"higgs_p": 2,
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"higgs_weight_bits": 4,
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"batch_size": 1,
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"device": "cuda",
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| 59 |
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"device_map": null,
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"save_fns": [
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"transformers_higgs"
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],
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"load_fns": [
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"transformers_higgs"
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],
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"reapply_after_load": {
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"factorizer": null,
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| 68 |
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"pruner": null,
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"quantizer": null,
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| 70 |
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"distiller": null,
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| 71 |
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"kernel": null,
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| 72 |
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"cacher": null,
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| 73 |
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"recoverer": null,
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| 74 |
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"distributer": null,
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| 75 |
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"compiler": null,
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| 76 |
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"batcher": null,
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| 77 |
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"enhancer": null
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| 78 |
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}
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| 79 |
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}
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```
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| 81 |
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| 82 |
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## 🌍 Join the Pruna AI community!
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| 83 |
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| 84 |
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[](https://twitter.com/PrunaAI)
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| 85 |
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[](https://github.com/PrunaAI)
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| 86 |
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[](https://www.linkedin.com/company/93832878/admin/feed/posts/?feedType=following)
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| 87 |
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[](https://discord.gg/JFQmtFKCjd)
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| 88 |
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[](https://www.reddit.com/r/PrunaAI/)
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config.json
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@@ -0,0 +1,1284 @@
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|
| 1 |
+
{
|
| 2 |
+
"architectures": [
|
| 3 |
+
"LlamaForCausalLM"
|
| 4 |
+
],
|
| 5 |
+
"attention_bias": false,
|
| 6 |
+
"attention_dropout": 0.0,
|
| 7 |
+
"bos_token_id": 128000,
|
| 8 |
+
"eos_token_id": [
|
| 9 |
+
128001,
|
| 10 |
+
128008,
|
| 11 |
+
128009
|
| 12 |
+
],
|
| 13 |
+
"head_dim": 64,
|
| 14 |
+
"hidden_act": "silu",
|
| 15 |
+
"hidden_size": 2048,
|
| 16 |
+
"initializer_range": 0.02,
|
| 17 |
+
"intermediate_size": 8192,
|
| 18 |
+
"max_position_embeddings": 131072,
|
| 19 |
+
"mlp_bias": false,
|
| 20 |
+
"model_type": "llama",
|
| 21 |
+
"num_attention_heads": 32,
|
| 22 |
+
"num_hidden_layers": 16,
|
| 23 |
+
"num_key_value_heads": 8,
|
| 24 |
+
"pretraining_tp": 1,
|
| 25 |
+
"quantization_config": {
|
| 26 |
+
"bits": 4,
|
| 27 |
+
"example_batch_size": 1,
|
| 28 |
+
"group_size": 256,
|
| 29 |
+
"hadamard_size": 1024,
|
| 30 |
+
"modules_to_not_convert": [
|
| 31 |
+
"lm_head"
|
| 32 |
+
],
|
| 33 |
+
"p": 2,
|
| 34 |
+
"quant_method": "higgs",
|
| 35 |
+
"tune_metadata": {
|
| 36 |
+
"model.layers.0.mlp.down_proj": {
|
| 37 |
+
"K": 8192,
|
| 38 |
+
"M": 1,
|
| 39 |
+
"N": 2048,
|
| 40 |
+
"device": "cuda:0",
|
| 41 |
+
"dtype": "torch.bfloat16",
|
| 42 |
+
"group_size": 256,
|
| 43 |
+
"num_bits": 4,
|
| 44 |
+
"num_sms": 114,
|
| 45 |
+
"template_id": 136
|
| 46 |
+
},
|
| 47 |
+
"model.layers.0.mlp.gate_proj": {
|
| 48 |
+
"K": 2048,
|
| 49 |
+
"M": 1,
|
| 50 |
+
"N": 8192,
|
| 51 |
+
"device": "cuda:0",
|
| 52 |
+
"dtype": "torch.bfloat16",
|
| 53 |
+
"group_size": 256,
|
| 54 |
+
"num_bits": 4,
|
| 55 |
+
"num_sms": 114,
|
| 56 |
+
"template_id": 136
|
| 57 |
+
},
|
| 58 |
+
"model.layers.0.mlp.up_proj": {
|
| 59 |
+
"K": 2048,
|
| 60 |
+
"M": 1,
|
| 61 |
+
"N": 8192,
|
| 62 |
+
"device": "cuda:0",
|
| 63 |
+
"dtype": "torch.bfloat16",
|
| 64 |
+
"group_size": 256,
|
| 65 |
+
"num_bits": 4,
|
| 66 |
+
"num_sms": 114,
|
| 67 |
+
"template_id": 136
|
| 68 |
+
},
|
| 69 |
+
"model.layers.0.self_attn.k_proj": {
|
| 70 |
+
"K": 2048,
|
| 71 |
+
"M": 1,
|
| 72 |
+
"N": 512,
|
| 73 |
+
"device": "cuda:0",
|
| 74 |
+
"dtype": "torch.bfloat16",
|
| 75 |
+
"group_size": 256,
|
| 76 |
+
"num_bits": 4,
|
| 77 |
+
"num_sms": 114,
|
| 78 |
+
"template_id": 36
|
| 79 |
+
},
|
| 80 |
+
"model.layers.0.self_attn.o_proj": {
|
| 81 |
+
"K": 2048,
|
| 82 |
+
"M": 1,
|
| 83 |
+
"N": 2048,
|
| 84 |
+
"device": "cuda:0",
|
| 85 |
+
"dtype": "torch.bfloat16",
|
| 86 |
+
"group_size": 256,
|
| 87 |
+
"num_bits": 4,
|
| 88 |
+
"num_sms": 114,
|
| 89 |
+
"template_id": 88
|
| 90 |
+
},
|
| 91 |
+
"model.layers.0.self_attn.q_proj": {
|
| 92 |
+
"K": 2048,
|
| 93 |
+
"M": 1,
|
| 94 |
+
"N": 2048,
|
| 95 |
+
"device": "cuda:0",
|
| 96 |
+
"dtype": "torch.bfloat16",
|
| 97 |
+
"group_size": 256,
|
| 98 |
+
"num_bits": 4,
|
| 99 |
+
"num_sms": 114,
|
| 100 |
+
"template_id": 88
|
| 101 |
+
},
|
| 102 |
+
"model.layers.0.self_attn.v_proj": {
|
| 103 |
+
"K": 2048,
|
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},
|
| 1270 |
+
"rms_norm_eps": 1e-05,
|
| 1271 |
+
"rope_scaling": {
|
| 1272 |
+
"factor": 32.0,
|
| 1273 |
+
"high_freq_factor": 4.0,
|
| 1274 |
+
"low_freq_factor": 1.0,
|
| 1275 |
+
"original_max_position_embeddings": 8192,
|
| 1276 |
+
"rope_type": "llama3"
|
| 1277 |
+
},
|
| 1278 |
+
"rope_theta": 500000.0,
|
| 1279 |
+
"tie_word_embeddings": true,
|
| 1280 |
+
"torch_dtype": "bfloat16",
|
| 1281 |
+
"transformers_version": "4.52.4",
|
| 1282 |
+
"use_cache": true,
|
| 1283 |
+
"vocab_size": 128256
|
| 1284 |
+
}
|
generation_config.json
ADDED
|
@@ -0,0 +1,12 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"bos_token_id": 128000,
|
| 3 |
+
"do_sample": true,
|
| 4 |
+
"eos_token_id": [
|
| 5 |
+
128001,
|
| 6 |
+
128008,
|
| 7 |
+
128009
|
| 8 |
+
],
|
| 9 |
+
"temperature": 0.6,
|
| 10 |
+
"top_p": 0.9,
|
| 11 |
+
"transformers_version": "4.52.4"
|
| 12 |
+
}
|
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:c594ec0bd527139a6e77dbcb624029500e83007ada4bbb1c0cf18fb4f6936dc5
|
| 3 |
+
size 556243632
|
smash_config.json
ADDED
|
@@ -0,0 +1,39 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"batcher": null,
|
| 3 |
+
"cacher": null,
|
| 4 |
+
"compiler": null,
|
| 5 |
+
"distiller": null,
|
| 6 |
+
"distributer": null,
|
| 7 |
+
"enhancer": null,
|
| 8 |
+
"factorizer": null,
|
| 9 |
+
"kernel": null,
|
| 10 |
+
"pruner": null,
|
| 11 |
+
"quantizer": "higgs",
|
| 12 |
+
"recoverer": null,
|
| 13 |
+
"higgs_group_size": 256,
|
| 14 |
+
"higgs_hadamard_size": 1024,
|
| 15 |
+
"higgs_p": 2,
|
| 16 |
+
"higgs_weight_bits": 4,
|
| 17 |
+
"batch_size": 1,
|
| 18 |
+
"device": "cuda",
|
| 19 |
+
"device_map": null,
|
| 20 |
+
"save_fns": [
|
| 21 |
+
"transformers_higgs"
|
| 22 |
+
],
|
| 23 |
+
"load_fns": [
|
| 24 |
+
"transformers_higgs"
|
| 25 |
+
],
|
| 26 |
+
"reapply_after_load": {
|
| 27 |
+
"factorizer": null,
|
| 28 |
+
"pruner": null,
|
| 29 |
+
"quantizer": null,
|
| 30 |
+
"distiller": null,
|
| 31 |
+
"kernel": null,
|
| 32 |
+
"cacher": null,
|
| 33 |
+
"recoverer": null,
|
| 34 |
+
"distributer": null,
|
| 35 |
+
"compiler": null,
|
| 36 |
+
"batcher": null,
|
| 37 |
+
"enhancer": null
|
| 38 |
+
}
|
| 39 |
+
}
|