Upload folder using huggingface_hub (#2)
Browse files- 3ccbc6d4ef9e59b43dffbdd1498ab1b69ca057b20a065c6aee52e6e3a06c904b (ae69299e9c6419dbc3b7367d0ba6733e1a765e87)
- d22c1e29105fc7655b779517f18f50232c020c1f50793f2e349eaeb2a3f18afd (24b669296002c505f85289da09814038ec56ce03)
- README.md +4 -3
- config.json +2 -2
- plots.png +0 -0
- smash_config.json +1 -1
README.md
CHANGED
@@ -1,5 +1,4 @@
|
|
1 |
---
|
2 |
-
library_name: pruna-engine
|
3 |
thumbnail: "https://assets-global.website-files.com/646b351987a8d8ce158d1940/64ec9e96b4334c0e1ac41504_Logo%20with%20white%20text.svg"
|
4 |
metrics:
|
5 |
- memory_disk
|
@@ -8,6 +7,8 @@ metrics:
|
|
8 |
- inference_throughput
|
9 |
- inference_CO2_emissions
|
10 |
- inference_energy_consumption
|
|
|
|
|
11 |
---
|
12 |
<!-- header start -->
|
13 |
<!-- 200823 -->
|
@@ -33,7 +34,7 @@ metrics:
|
|
33 |
|
34 |
## Results
|
35 |
|
36 |
-
|
37 |
|
38 |
**Frequently Asked Questions**
|
39 |
- ***How does the compression work?*** The model is compressed with llm-int8.
|
@@ -60,7 +61,7 @@ You can run the smashed model with these steps:
|
|
60 |
from transformers import AutoModelForCausalLM, AutoTokenizer
|
61 |
|
62 |
model = AutoModelForCausalLM.from_pretrained("PrunaAI/KoboldAI-GPT-J-6B-Janeway-bnb-8bit-smashed",
|
63 |
-
trust_remote_code=True)
|
64 |
tokenizer = AutoTokenizer.from_pretrained("KoboldAI/GPT-J-6B-Janeway")
|
65 |
|
66 |
input_ids = tokenizer("What is the color of prunes?,", return_tensors='pt').to(model.device)["input_ids"]
|
|
|
1 |
---
|
|
|
2 |
thumbnail: "https://assets-global.website-files.com/646b351987a8d8ce158d1940/64ec9e96b4334c0e1ac41504_Logo%20with%20white%20text.svg"
|
3 |
metrics:
|
4 |
- memory_disk
|
|
|
7 |
- inference_throughput
|
8 |
- inference_CO2_emissions
|
9 |
- inference_energy_consumption
|
10 |
+
tags:
|
11 |
+
- pruna-ai
|
12 |
---
|
13 |
<!-- header start -->
|
14 |
<!-- 200823 -->
|
|
|
34 |
|
35 |
## Results
|
36 |
|
37 |
+
![image info](./plots.png)
|
38 |
|
39 |
**Frequently Asked Questions**
|
40 |
- ***How does the compression work?*** The model is compressed with llm-int8.
|
|
|
61 |
from transformers import AutoModelForCausalLM, AutoTokenizer
|
62 |
|
63 |
model = AutoModelForCausalLM.from_pretrained("PrunaAI/KoboldAI-GPT-J-6B-Janeway-bnb-8bit-smashed",
|
64 |
+
trust_remote_code=True, device_map='auto')
|
65 |
tokenizer = AutoTokenizer.from_pretrained("KoboldAI/GPT-J-6B-Janeway")
|
66 |
|
67 |
input_ids = tokenizer("What is the color of prunes?,", return_tensors='pt').to(model.device)["input_ids"]
|
config.json
CHANGED
@@ -1,5 +1,5 @@
|
|
1 |
{
|
2 |
-
"_name_or_path": "/tmp/
|
3 |
"activation_function": "gelu_new",
|
4 |
"antemplate": "[Genre: <|>]",
|
5 |
"architectures": [
|
@@ -21,7 +21,7 @@
|
|
21 |
"quantization_config": {
|
22 |
"bnb_4bit_compute_dtype": "bfloat16",
|
23 |
"bnb_4bit_quant_type": "fp4",
|
24 |
-
"bnb_4bit_use_double_quant":
|
25 |
"llm_int8_enable_fp32_cpu_offload": false,
|
26 |
"llm_int8_has_fp16_weight": false,
|
27 |
"llm_int8_skip_modules": [
|
|
|
1 |
{
|
2 |
+
"_name_or_path": "/tmp/tmpxd_m1_d_",
|
3 |
"activation_function": "gelu_new",
|
4 |
"antemplate": "[Genre: <|>]",
|
5 |
"architectures": [
|
|
|
21 |
"quantization_config": {
|
22 |
"bnb_4bit_compute_dtype": "bfloat16",
|
23 |
"bnb_4bit_quant_type": "fp4",
|
24 |
+
"bnb_4bit_use_double_quant": false,
|
25 |
"llm_int8_enable_fp32_cpu_offload": false,
|
26 |
"llm_int8_has_fp16_weight": false,
|
27 |
"llm_int8_skip_modules": [
|
plots.png
ADDED
smash_config.json
CHANGED
@@ -8,7 +8,7 @@
|
|
8 |
"compilers": "None",
|
9 |
"task": "text_text_generation",
|
10 |
"device": "cuda",
|
11 |
-
"cache_dir": "/ceph/hdd/staff/charpent/.cache/
|
12 |
"batch_size": 1,
|
13 |
"model_name": "KoboldAI/GPT-J-6B-Janeway",
|
14 |
"pruning_ratio": 0.0,
|
|
|
8 |
"compilers": "None",
|
9 |
"task": "text_text_generation",
|
10 |
"device": "cuda",
|
11 |
+
"cache_dir": "/ceph/hdd/staff/charpent/.cache/modelsbywxjj85",
|
12 |
"batch_size": 1,
|
13 |
"model_name": "KoboldAI/GPT-J-6B-Janeway",
|
14 |
"pruning_ratio": 0.0,
|