Upload folder using huggingface_hub

#1
.gitattributes CHANGED
@@ -33,3 +33,22 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
36
+ microsoft_WizardLM-2-7B.IQ3_M.gguf filter=lfs diff=lfs merge=lfs -text
37
+ microsoft_WizardLM-2-7B.IQ3_S.gguf filter=lfs diff=lfs merge=lfs -text
38
+ microsoft_WizardLM-2-7B.IQ3_XS.gguf filter=lfs diff=lfs merge=lfs -text
39
+ microsoft_WizardLM-2-7B.IQ4_NL.gguf filter=lfs diff=lfs merge=lfs -text
40
+ microsoft_WizardLM-2-7B.IQ4_XS.gguf filter=lfs diff=lfs merge=lfs -text
41
+ microsoft_WizardLM-2-7B.Q2_K.gguf filter=lfs diff=lfs merge=lfs -text
42
+ microsoft_WizardLM-2-7B.Q3_K_L.gguf filter=lfs diff=lfs merge=lfs -text
43
+ microsoft_WizardLM-2-7B.Q3_K_M.gguf filter=lfs diff=lfs merge=lfs -text
44
+ microsoft_WizardLM-2-7B.Q3_K_S.gguf filter=lfs diff=lfs merge=lfs -text
45
+ microsoft_WizardLM-2-7B.Q4_0.gguf filter=lfs diff=lfs merge=lfs -text
46
+ microsoft_WizardLM-2-7B.Q4_1.gguf filter=lfs diff=lfs merge=lfs -text
47
+ microsoft_WizardLM-2-7B.Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
48
+ microsoft_WizardLM-2-7B.Q4_K_S.gguf filter=lfs diff=lfs merge=lfs -text
49
+ microsoft_WizardLM-2-7B.Q5_0.gguf filter=lfs diff=lfs merge=lfs -text
50
+ microsoft_WizardLM-2-7B.Q5_1.gguf filter=lfs diff=lfs merge=lfs -text
51
+ microsoft_WizardLM-2-7B.Q5_K_M.gguf filter=lfs diff=lfs merge=lfs -text
52
+ microsoft_WizardLM-2-7B.Q5_K_S.gguf filter=lfs diff=lfs merge=lfs -text
53
+ microsoft_WizardLM-2-7B.Q6_K.gguf filter=lfs diff=lfs merge=lfs -text
54
+ microsoft_WizardLM-2-7B.Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,219 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ thumbnail: "https://assets-global.website-files.com/646b351987a8d8ce158d1940/64ec9e96b4334c0e1ac41504_Logo%20with%20white%20text.svg"
3
+ metrics:
4
+ - memory_disk
5
+ - memory_inference
6
+ - inference_latency
7
+ - inference_throughput
8
+ - inference_CO2_emissions
9
+ - inference_energy_consumption
10
+ tags:
11
+ - pruna-ai
12
+ ---
13
+ <!-- header start -->
14
+ <!-- 200823 -->
15
+ <div style="width: auto; margin-left: auto; margin-right: auto">
16
+ <a href="https://www.pruna.ai/" target="_blank" rel="noopener noreferrer">
17
+ <img src="https://i.imgur.com/eDAlcgk.png" alt="PrunaAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
18
+ </a>
19
+ </div>
20
+ <!-- header end -->
21
+
22
+ [![Twitter](https://img.shields.io/twitter/follow/PrunaAI?style=social)](https://twitter.com/PrunaAI)
23
+ [![GitHub](https://img.shields.io/github/followers/PrunaAI?label=Follow%20%40PrunaAI&style=social)](https://github.com/PrunaAI)
24
+ [![LinkedIn](https://img.shields.io/badge/LinkedIn-Connect-blue)](https://www.linkedin.com/company/93832878/admin/feed/posts/?feedType=following)
25
+ [![Discord](https://img.shields.io/badge/Discord-Join%20Us-blue?style=social&logo=discord)](https://discord.gg/CP4VSgck)
26
+
27
+ # Simply make AI models cheaper, smaller, faster, and greener!
28
+
29
+ - Give a thumbs up if you like this model!
30
+ - Contact us and tell us which model to compress next [here](https://www.pruna.ai/contact).
31
+ - Request access to easily compress your *own* AI models [here](https://z0halsaff74.typeform.com/pruna-access?typeform-source=www.pruna.ai).
32
+ - Read the documentations to know more [here](https://pruna-ai-pruna.readthedocs-hosted.com/en/latest/)
33
+ - Join Pruna AI community on Discord [here](https://discord.gg/CP4VSgck) to share feedback/suggestions or get help.
34
+
35
+ **Frequently Asked Questions**
36
+ - ***How does the compression work?*** The model is compressed with GGUF.
37
+ - ***How does the model quality change?*** The quality of the model output might vary compared to the base model.
38
+ - ***What is the model format?*** We use GGUF format.
39
+ - ***What calibration data has been used?*** If needed by the compression method, we used WikiText as the calibration data.
40
+ - ***How to compress my own models?*** You can request premium access to more compression methods and tech support for your specific use-cases [here](https://z0halsaff74.typeform.com/pruna-access?typeform-source=www.pruna.ai).
41
+
42
+ # Downloading and running the models
43
+
44
+ You can download the individual files from the Files & versions section. Here is a list of the different versions we provide. For more info checkout [this chart](https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9) and [this guide](https://www.reddit.com/r/LocalLLaMA/comments/1ba55rj/overview_of_gguf_quantization_methods/):
45
+
46
+ | Quant type | Description |
47
+ |------------|--------------------------------------------------------------------------------------------|
48
+ | Q5_K_M | High quality, recommended. |
49
+ | Q5_K_S | High quality, recommended. |
50
+ | Q4_K_M | Good quality, uses about 4.83 bits per weight, recommended. |
51
+ | Q4_K_S | Slightly lower quality with more space savings, recommended. |
52
+ | IQ4_NL | Decent quality, slightly smaller than Q4_K_S with similar performance, recommended. |
53
+ | IQ4_XS | Decent quality, smaller than Q4_K_S with similar performance, recommended. |
54
+ | Q3_K_L | Lower quality but usable, good for low RAM availability. |
55
+ | Q3_K_M | Even lower quality. |
56
+ | IQ3_M | Medium-low quality, new method with decent performance comparable to Q3_K_M. |
57
+ | IQ3_S | Lower quality, new method with decent performance, recommended over Q3_K_S quant, same size with better performance. |
58
+ | Q3_K_S | Low quality, not recommended. |
59
+ | IQ3_XS | Lower quality, new method with decent performance, slightly better than Q3_K_S. |
60
+ | Q2_K | Very low quality but surprisingly usable. |
61
+
62
+
63
+ ## How to download GGUF files ?
64
+
65
+ **Note for manual downloaders:** You almost never want to clone the entire repo! Multiple different quantisation formats are provided, and most users only want to pick and download a single file.
66
+
67
+ The following clients/libraries will automatically download models for you, providing a list of available models to choose from:
68
+
69
+ * LM Studio
70
+ * LoLLMS Web UI
71
+ * Faraday.dev
72
+
73
+ - **Option A** - Downloading in `text-generation-webui`:
74
+ - **Step 1**: Under Download Model, you can enter the model repo: PrunaAI/microsoft_WizardLM-2-7B-GGUF-smashed-smashed and below it, a specific filename to download, such as: phi-2.IQ3_M.gguf.
75
+ - **Step 2**: Then click Download.
76
+
77
+ - **Option B** - Downloading on the command line (including multiple files at once):
78
+ - **Step 1**: We recommend using the `huggingface-hub` Python library:
79
+ ```shell
80
+ pip3 install huggingface-hub
81
+ ```
82
+ - **Step 2**: Then you can download any individual model file to the current directory, at high speed, with a command like this:
83
+ ```shell
84
+ huggingface-cli download PrunaAI/microsoft_WizardLM-2-7B-GGUF-smashed-smashed microsoft_WizardLM-2-7B.IQ3_M.gguf --local-dir . --local-dir-use-symlinks False
85
+ ```
86
+ <details>
87
+ <summary>More advanced huggingface-cli download usage (click to read)</summary>
88
+ Alternatively, you can also download multiple files at once with a pattern:
89
+
90
+ ```shell
91
+ huggingface-cli download PrunaAI/microsoft_WizardLM-2-7B-GGUF-smashed-smashed --local-dir . --local-dir-use-symlinks False --include='*Q4_K*gguf'
92
+ ```
93
+
94
+ For more documentation on downloading with `huggingface-cli`, please see: [HF -> Hub Python Library -> Download files -> Download from the CLI](https://huggingface.co/docs/huggingface_hub/guides/download#download-from-the-cli).
95
+
96
+ To accelerate downloads on fast connections (1Gbit/s or higher), install `hf_transfer`:
97
+
98
+ ```shell
99
+ pip3 install hf_transfer
100
+ ```
101
+
102
+ And set environment variable `HF_HUB_ENABLE_HF_TRANSFER` to `1`:
103
+
104
+ ```shell
105
+ HF_HUB_ENABLE_HF_TRANSFER=1 huggingface-cli download PrunaAI/microsoft_WizardLM-2-7B-GGUF-smashed-smashed microsoft_WizardLM-2-7B.IQ3_M.gguf --local-dir . --local-dir-use-symlinks False
106
+ ```
107
+
108
+ Windows Command Line users: You can set the environment variable by running `set HF_HUB_ENABLE_HF_TRANSFER=1` before the download command.
109
+ </details>
110
+ <!-- README_GGUF.md-how-to-download end -->
111
+
112
+ <!-- README_GGUF.md-how-to-run start -->
113
+
114
+ ## How to run model in GGUF format?
115
+ - **Option A** - Introductory example with `llama.cpp` command
116
+
117
+ Make sure you are using `llama.cpp` from commit [d0cee0d](https://github.com/ggerganov/llama.cpp/commit/d0cee0d36d5be95a0d9088b674dbb27354107221) or later.
118
+
119
+ ```shell
120
+ ./main -ngl 35 -m microsoft_WizardLM-2-7B.IQ3_M.gguf --color -c 32768 --temp 0.7 --repeat_penalty 1.1 -n -1 -p "<s>[INST] {prompt\} [/INST]"
121
+ ```
122
+
123
+ Change `-ngl 32` to the number of layers to offload to GPU. Remove it if you don't have GPU acceleration.
124
+
125
+ Change `-c 32768` to the desired sequence length. For extended sequence models - eg 8K, 16K, 32K - the necessary RoPE scaling parameters are read from the GGUF file and set by llama.cpp automatically. Note that longer sequence lengths require much more resources, so you may need to reduce this value.
126
+
127
+ If you want to have a chat-style conversation, replace the `-p <PROMPT>` argument with `-i -ins`
128
+
129
+ For other parameters and how to use them, please refer to [the llama.cpp documentation](https://github.com/ggerganov/llama.cpp/blob/master/examples/main/README.md)
130
+
131
+ - **Option B** - Running in `text-generation-webui`
132
+
133
+ Further instructions can be found in the text-generation-webui documentation, here: [text-generation-webui/docs/04 ‐ Model Tab.md](https://github.com/oobabooga/text-generation-webui/blob/main/docs/04%20%E2%80%90%20Model%20Tab.md#llamacpp).
134
+
135
+ - **Option C** - Running from Python code
136
+
137
+ You can use GGUF models from Python using the [llama-cpp-python](https://github.com/abetlen/llama-cpp-python) or [ctransformers](https://github.com/marella/ctransformers) libraries. Note that at the time of writing (Nov 27th 2023), ctransformers has not been updated for some time and is not compatible with some recent models. Therefore I recommend you use llama-cpp-python.
138
+
139
+ ### How to load this model in Python code, using llama-cpp-python
140
+
141
+ For full documentation, please see: [llama-cpp-python docs](https://abetlen.github.io/llama-cpp-python/).
142
+
143
+ #### First install the package
144
+
145
+ Run one of the following commands, according to your system:
146
+
147
+ ```shell
148
+ # Base ctransformers with no GPU acceleration
149
+ pip install llama-cpp-python
150
+ # With NVidia CUDA acceleration
151
+ CMAKE_ARGS="-DLLAMA_CUBLAS=on" pip install llama-cpp-python
152
+ # Or with OpenBLAS acceleration
153
+ CMAKE_ARGS="-DLLAMA_BLAS=ON -DLLAMA_BLAS_VENDOR=OpenBLAS" pip install llama-cpp-python
154
+ # Or with CLBLast acceleration
155
+ CMAKE_ARGS="-DLLAMA_CLBLAST=on" pip install llama-cpp-python
156
+ # Or with AMD ROCm GPU acceleration (Linux only)
157
+ CMAKE_ARGS="-DLLAMA_HIPBLAS=on" pip install llama-cpp-python
158
+ # Or with Metal GPU acceleration for macOS systems only
159
+ CMAKE_ARGS="-DLLAMA_METAL=on" pip install llama-cpp-python
160
+
161
+ # In windows, to set the variables CMAKE_ARGS in PowerShell, follow this format; eg for NVidia CUDA:
162
+ $env:CMAKE_ARGS = "-DLLAMA_OPENBLAS=on"
163
+ pip install llama-cpp-python
164
+ ```
165
+
166
+ #### Simple llama-cpp-python example code
167
+
168
+ ```python
169
+ from llama_cpp import Llama
170
+
171
+ # Set gpu_layers to the number of layers to offload to GPU. Set to 0 if no GPU acceleration is available on your system.
172
+ llm = Llama(
173
+ model_path="./microsoft_WizardLM-2-7B.IQ3_M.gguf", # Download the model file first
174
+ n_ctx=32768, # The max sequence length to use - note that longer sequence lengths require much more resources
175
+ n_threads=8, # The number of CPU threads to use, tailor to your system and the resulting performance
176
+ n_gpu_layers=35 # The number of layers to offload to GPU, if you have GPU acceleration available
177
+ )
178
+
179
+ # Simple inference example
180
+ output = llm(
181
+ "<s>[INST] {prompt} [/INST]", # Prompt
182
+ max_tokens=512, # Generate up to 512 tokens
183
+ stop=["</s>"], # Example stop token - not necessarily correct for this specific model! Please check before using.
184
+ echo=True # Whether to echo the prompt
185
+ )
186
+
187
+ # Chat Completion API
188
+
189
+ llm = Llama(model_path="./microsoft_WizardLM-2-7B.IQ3_M.gguf", chat_format="llama-2") # Set chat_format according to the model you are using
190
+ llm.create_chat_completion(
191
+ messages = [
192
+ {"role": "system", "content": "You are a story writing assistant."},
193
+ {
194
+ "role": "user",
195
+ "content": "Write a story about llamas."
196
+ }
197
+ ]
198
+ )
199
+ ```
200
+
201
+ - **Option D** - Running with LangChain
202
+
203
+ Here are guides on using llama-cpp-python and ctransformers with LangChain:
204
+
205
+ * [LangChain + llama-cpp-python](https://python.langchain.com/docs/integrations/llms/llamacpp)
206
+ * [LangChain + ctransformers](https://python.langchain.com/docs/integrations/providers/ctransformers)
207
+
208
+ ## Configurations
209
+
210
+ The configuration info are in `smash_config.json`.
211
+
212
+ ## Credits & License
213
+
214
+ The license of the smashed model follows the license of the original model. Please check the license of the original model before using this model which provided the base model. The license of the `pruna-engine` is [here](https://pypi.org/project/pruna-engine/) on Pypi.
215
+
216
+ ## Want to compress other models?
217
+
218
+ - Contact us and tell us which model to compress next [here](https://www.pruna.ai/contact).
219
+ - Request access to easily compress your own AI models [here](https://z0halsaff74.typeform.com/pruna-access?typeform-source=www.pruna.ai).
microsoft_WizardLM-2-7B.IQ3_M.gguf ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1e329f490265b2353bc3fdb78be0bc0e892e92857f9c323e51e750d44ff008b3
3
+ size 3284892224
microsoft_WizardLM-2-7B.IQ3_S.gguf ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:871793d0f45b87be6de4ef4c4ed6650b4645ebc0705a15b47d1f4788ebfa7088
3
+ size 3182393920
microsoft_WizardLM-2-7B.IQ3_XS.gguf ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6a46c843108d65c0eea7ad0e5d884033c188e0be84340b44a164e3fd37f2a129
3
+ size 3018816064
microsoft_WizardLM-2-7B.IQ4_NL.gguf ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:fb239b7c21cb06acbb0d431ceae72a4e8f3c5a8b91f37996192c396ac0c2cc45
3
+ size 4155054656
microsoft_WizardLM-2-7B.IQ4_XS.gguf ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f18b7970d62653049751a71b9e09ef30c35cba12c69ada8bb356d7c2fdba51c9
3
+ size 3944389184
microsoft_WizardLM-2-7B.Q2_K.gguf ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:52f57f6a1599e9de92e5d98ec6d8e44e396b2423d3069c26aeee2632ff87a85d
3
+ size 2719242816
microsoft_WizardLM-2-7B.Q3_K_L.gguf ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:82185759943a995241591416fe80981470952869299eb9e6e06579e18f48db50
3
+ size 3822025280
microsoft_WizardLM-2-7B.Q3_K_M.gguf ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:afea5f6a6a8d20d80ddb23c04080750265042f1f68b8ba75f64d36255693896c
3
+ size 3518986816
microsoft_WizardLM-2-7B.Q3_K_S.gguf ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6d0529a5f90b6b0f3f27398278e6361fa0704edae09434cfdc73bbe7dabe99d7
3
+ size 3164568128
microsoft_WizardLM-2-7B.Q4_0.gguf ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:faed6eef46f3f350edede483a2cb12d9be57a6dc61cfa2db0b2668c48114681a
3
+ size 4108917312
microsoft_WizardLM-2-7B.Q4_1.gguf ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1a825db64d19cb83fcf7a55a23a43d19a3d3238fac37d3bb7d82caf00de39678
3
+ size 4553316928
microsoft_WizardLM-2-7B.Q4_K_M.gguf ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:bcb7384f2ef067ad5535964ee3b9645502e9951180f3f547108c757f675c7e80
3
+ size 4368439872
microsoft_WizardLM-2-7B.Q4_K_S.gguf ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a5ab668e3a194825bde05cdb1be19c90622db1a66ba1d095eb04f3ab471f4674
3
+ size 4140374592
microsoft_WizardLM-2-7B.Q5_0.gguf ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b8325fdc2ec8ad3ed0497df9da9c2da61557b7cef12db8085ff6d504c604ee8a
3
+ size 4997716544
microsoft_WizardLM-2-7B.Q5_1.gguf ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:41f532533b3db47b4e06e71b6adfb18b5fb84c469e4bf004634ec66960798308
3
+ size 5442116160
microsoft_WizardLM-2-7B.Q5_K_M.gguf ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:751be20d84f2ff4bb406b4e99aa347fed1801a1e83785ce5a7dbaf3fd8dc8080
3
+ size 5131409984
microsoft_WizardLM-2-7B.Q5_K_S.gguf ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:8a9af0d9397dbfaa59fd2b7194eb78d9f7bbb67eb4173358c6ba5decab840460
3
+ size 4997716544
microsoft_WizardLM-2-7B.Q6_K.gguf ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f8d670c7ca5a5eaf5abef07e1af0fc4132606b4f1889067eee00b5784ded7a6e
3
+ size 5942065728
microsoft_WizardLM-2-7B.Q8_0.gguf ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:7c1322b6c69461c4be9211f3593f3e2b73701787ec68d2e90b8d500a7bb17a08
3
+ size 7695858240
microsoft_WizardLM-2-7B.fp16.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:3be7cdb745a991fb39cbfe15fdce67d750c31f3ba8e8311a63143fd50bcc0594
3
+ size 14484733152