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1
  ---
 
2
  datasets:
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  - garage-bAInd/Open-Platypus
4
  inference: false
5
  language:
6
  - en
7
- license: llama2
8
  model_creator: garage-bAInd
9
- model_link: https://huggingface.co/garage-bAInd/Camel-Platypus2-70B
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  model_name: Camel Platypus2 70B
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  model_type: llama
 
 
 
 
 
 
 
 
 
 
 
 
12
  quantized_by: TheBloke
13
  ---
14
 
@@ -44,9 +56,9 @@ Multiple GPTQ parameter permutations are provided; see Provided Files below for
44
  <!-- repositories-available start -->
45
  ## Repositories available
46
 
 
47
  * [GPTQ models for GPU inference, with multiple quantisation parameter options.](https://huggingface.co/TheBloke/Camel-Platypus2-70B-GPTQ)
48
  * [2, 3, 4, 5, 6 and 8-bit GGUF models for CPU+GPU inference](https://huggingface.co/TheBloke/Camel-Platypus2-70B-GGUF)
49
- * [2, 3, 4, 5, 6 and 8-bit GGML models for CPU+GPU inference (deprecated)](https://huggingface.co/TheBloke/Camel-Platypus2-70B-GGML)
50
  * [garage-bAInd's original unquantised fp16 model in pytorch format, for GPU inference and for further conversions](https://huggingface.co/garage-bAInd/Camel-Platypus2-70B)
51
  <!-- repositories-available end -->
52
 
@@ -64,7 +76,15 @@ Below is an instruction that describes a task. Write a response that appropriate
64
  ```
65
 
66
  <!-- prompt-template end -->
 
 
 
 
67
 
 
 
 
 
68
  <!-- README_GPTQ.md-provided-files start -->
69
  ## Provided files and GPTQ parameters
70
 
@@ -89,22 +109,22 @@ All recent GPTQ files are made with AutoGPTQ, and all files in non-main branches
89
 
90
  | Branch | Bits | GS | Act Order | Damp % | GPTQ Dataset | Seq Len | Size | ExLlama | Desc |
91
  | ------ | ---- | -- | --------- | ------ | ------------ | ------- | ---- | ------- | ---- |
92
- | [main](https://huggingface.co/TheBloke/Camel-Platypus2-70B-GPTQ/tree/main) | 4 | None | Yes | 0.1 | [wikitext](https://huggingface.co/datasets/wikitext/viewer/wikitext-2-v1/test) | 4096 | 35.33 GB | Yes | Most compatible option. Good inference speed in AutoGPTQ and GPTQ-for-LLaMa. Lower inference quality than other options. |
93
- | [gptq-4bit-32g-actorder_True](https://huggingface.co/TheBloke/Camel-Platypus2-70B-GPTQ/tree/gptq-4bit-32g-actorder_True) | 4 | 32 | Yes | 0.1 | [wikitext](https://huggingface.co/datasets/wikitext/viewer/wikitext-2-v1/test) | 4096 | 40.66 GB | Yes | 4-bit, with Act Order and group size 32g. Gives highest possible inference quality, with maximum VRAM usage. Poor AutoGPTQ CUDA speed. |
94
- | [gptq-4bit-64g-actorder_True](https://huggingface.co/TheBloke/Camel-Platypus2-70B-GPTQ/tree/gptq-4bit-64g-actorder_True) | 4 | 64 | Yes | 0.1 | [wikitext](https://huggingface.co/datasets/wikitext/viewer/wikitext-2-v1/test) | 4096 | 37.99 GB | Yes | 4-bit, with Act Order and group size 64g. Uses less VRAM than 32g, but with slightly lower accuracy. Poor AutoGPTQ CUDA speed. |
95
- | [gptq-4bit-128g-actorder_True](https://huggingface.co/TheBloke/Camel-Platypus2-70B-GPTQ/tree/gptq-4bit-128g-actorder_True) | 4 | 128 | Yes | 0.1 | [wikitext](https://huggingface.co/datasets/wikitext/viewer/wikitext-2-v1/test) | 4096 | 36.65 GB | Yes | 4-bit, with Act Order and group size 128g. Uses even less VRAM than 64g, but with slightly lower accuracy. Poor AutoGPTQ CUDA speed. |
96
  | [gptq-3bit--1g-actorder_True](https://huggingface.co/TheBloke/Camel-Platypus2-70B-GPTQ/tree/gptq-3bit--1g-actorder_True) | 3 | None | Yes | 0.1 | [wikitext](https://huggingface.co/datasets/wikitext/viewer/wikitext-2-v1/test) | 4096 | 26.77 GB | No | 3-bit, with Act Order and no group size. Lowest possible VRAM requirements. May be lower quality than 3-bit 128g. |
97
- | [gptq-3bit-128g-actorder_True](https://huggingface.co/TheBloke/Camel-Platypus2-70B-GPTQ/tree/gptq-3bit-128g-actorder_True) | 3 | 128 | Yes | 0.1 | [wikitext](https://huggingface.co/datasets/wikitext/viewer/wikitext-2-v1/test) | 4096 | 28.03 GB | No | 3-bit, with group size 128g and act-order. Higher quality than 128g-False but poor AutoGPTQ CUDA speed. |
98
 
99
  <!-- README_GPTQ.md-provided-files end -->
100
 
101
  <!-- README_GPTQ.md-download-from-branches start -->
102
  ## How to download from branches
103
 
104
- - In text-generation-webui, you can add `:branch` to the end of the download name, eg `TheBloke/Camel-Platypus2-70B-GPTQ:gptq-4bit-32g-actorder_True`
105
  - With Git, you can clone a branch with:
106
  ```
107
- git clone --single-branch --branch gptq-4bit-32g-actorder_True https://huggingface.co/TheBloke/Camel-Platypus2-70B-GPTQ
108
  ```
109
  - In Python Transformers code, the branch is the `revision` parameter; see below.
110
  <!-- README_GPTQ.md-download-from-branches end -->
@@ -117,7 +137,7 @@ It is strongly recommended to use the text-generation-webui one-click-installers
117
 
118
  1. Click the **Model tab**.
119
  2. Under **Download custom model or LoRA**, enter `TheBloke/Camel-Platypus2-70B-GPTQ`.
120
- - To download from a specific branch, enter for example `TheBloke/Camel-Platypus2-70B-GPTQ:gptq-4bit-32g-actorder_True`
121
  - see Provided Files above for the list of branches for each option.
122
  3. Click **Download**.
123
  4. The model will start downloading. Once it's finished it will say "Done".
@@ -165,10 +185,10 @@ from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
165
 
166
  model_name_or_path = "TheBloke/Camel-Platypus2-70B-GPTQ"
167
  # To use a different branch, change revision
168
- # For example: revision="gptq-4bit-32g-actorder_True"
169
  model = AutoModelForCausalLM.from_pretrained(model_name_or_path,
170
- torch_dtype=torch.float16,
171
  device_map="auto",
 
172
  revision="main")
173
 
174
  tokenizer = AutoTokenizer.from_pretrained(model_name_or_path, use_fast=True)
@@ -186,7 +206,7 @@ prompt_template=f'''Below is an instruction that describes a task. Write a respo
186
  print("\n\n*** Generate:")
187
 
188
  input_ids = tokenizer(prompt_template, return_tensors='pt').input_ids.cuda()
189
- output = model.generate(inputs=input_ids, temperature=0.7, max_new_tokens=512)
190
  print(tokenizer.decode(output[0]))
191
 
192
  # Inference can also be done using transformers' pipeline
@@ -197,9 +217,11 @@ pipe = pipeline(
197
  model=model,
198
  tokenizer=tokenizer,
199
  max_new_tokens=512,
 
200
  temperature=0.7,
201
  top_p=0.95,
202
- repetition_penalty=1.15
 
203
  )
204
 
205
  print(pipe(prompt_template)[0]['generated_text'])
@@ -224,10 +246,12 @@ For further support, and discussions on these models and AI in general, join us
224
 
225
  [TheBloke AI's Discord server](https://discord.gg/theblokeai)
226
 
227
- ## Thanks, and how to contribute.
228
 
229
  Thanks to the [chirper.ai](https://chirper.ai) team!
230
 
 
 
231
  I've had a lot of people ask if they can contribute. I enjoy providing models and helping people, and would love to be able to spend even more time doing it, as well as expanding into new projects like fine tuning/training.
232
 
233
  If you're able and willing to contribute it will be most gratefully received and will help me to keep providing more models, and to start work on new AI projects.
@@ -239,7 +263,7 @@ Donaters will get priority support on any and all AI/LLM/model questions and req
239
 
240
  **Special thanks to**: Aemon Algiz.
241
 
242
- **Patreon special mentions**: Russ Johnson, J, alfie_i, Alex, NimbleBox.ai, Chadd, Mandus, Nikolai Manek, Ken Nordquist, ya boyyy, Illia Dulskyi, Viktor Bowallius, vamX, Iucharbius, zynix, Magnesian, Clay Pascal, Pierre Kircher, Enrico Ros, Tony Hughes, Elle, Andrey, knownsqashed, Deep Realms, Jerry Meng, Lone Striker, Derek Yates, Pyrater, Mesiah Bishop, James Bentley, Femi Adebogun, Brandon Frisco, SuperWojo, Alps Aficionado, Michael Dempsey, Vitor Caleffi, Will Dee, Edmond Seymore, usrbinkat, LangChain4j, Kacper Wikieł, Luke Pendergrass, John Detwiler, theTransient, Nathan LeClaire, Tiffany J. Kim, biorpg, Eugene Pentland, Stanislav Ovsiannikov, Fred von Graf, terasurfer, Kalila, Dan Guido, Nitin Borwankar, 阿明, Ai Maven, John Villwock, Gabriel Puliatti, Stephen Murray, Asp the Wyvern, danny, Chris Smitley, ReadyPlayerEmma, S_X, Daniel P. Andersen, Olakabola, Jeffrey Morgan, Imad Khwaja, Caitlyn Gatomon, webtim, Alicia Loh, Trenton Dambrowitz, Swaroop Kallakuri, Erik Bjäreholt, Leonard Tan, Spiking Neurons AB, Luke @flexchar, Ajan Kanaga, Thomas Belote, Deo Leter, RoA, Willem Michiel, transmissions 11, subjectnull, Matthew Berman, Joseph William Delisle, David Ziegler, Michael Davis, Johann-Peter Hartmann, Talal Aujan, senxiiz, Artur Olbinski, Rainer Wilmers, Spencer Kim, Fen Risland, Cap'n Zoog, Rishabh Srivastava, Michael Levine, Geoffrey Montalvo, Sean Connelly, Alexandros Triantafyllidis, Pieter, Gabriel Tamborski, Sam, Subspace Studios, Junyu Yang, Pedro Madruga, Vadim, Cory Kujawski, K, Raven Klaugh, Randy H, Mano Prime, Sebastain Graf, Space Cruiser
243
 
244
 
245
  Thank you to all my generous patrons and donaters!
 
1
  ---
2
+ base_model: https://huggingface.co/garage-bAInd/Camel-Platypus2-70B
3
  datasets:
4
  - garage-bAInd/Open-Platypus
5
  inference: false
6
  language:
7
  - en
8
+ license: cc-by-nc-4.0
9
  model_creator: garage-bAInd
 
10
  model_name: Camel Platypus2 70B
11
  model_type: llama
12
+ prompt_template: 'Below is an instruction that describes a task. Write a response
13
+ that appropriately completes the request.
14
+
15
+
16
+ ### Instruction:
17
+
18
+ {prompt}
19
+
20
+
21
+ ### Response:
22
+
23
+ '
24
  quantized_by: TheBloke
25
  ---
26
 
 
56
  <!-- repositories-available start -->
57
  ## Repositories available
58
 
59
+ * [AWQ model(s) for GPU inference.](https://huggingface.co/TheBloke/Camel-Platypus2-70B-AWQ)
60
  * [GPTQ models for GPU inference, with multiple quantisation parameter options.](https://huggingface.co/TheBloke/Camel-Platypus2-70B-GPTQ)
61
  * [2, 3, 4, 5, 6 and 8-bit GGUF models for CPU+GPU inference](https://huggingface.co/TheBloke/Camel-Platypus2-70B-GGUF)
 
62
  * [garage-bAInd's original unquantised fp16 model in pytorch format, for GPU inference and for further conversions](https://huggingface.co/garage-bAInd/Camel-Platypus2-70B)
63
  <!-- repositories-available end -->
64
 
 
76
  ```
77
 
78
  <!-- prompt-template end -->
79
+ <!-- licensing start -->
80
+ ## Licensing
81
+
82
+ The creator of the source model has listed its license as `cc-by-nc-4.0`, and this quantization has therefore used that same license.
83
 
84
+ As this model is based on Llama 2, it is also subject to the Meta Llama 2 license terms, and the license files for that are additionally included. It should therefore be considered as being claimed to be licensed under both licenses. I contacted Hugging Face for clarification on dual licensing but they do not yet have an official position. Should this change, or should Meta provide any feedback on this situation, I will update this section accordingly.
85
+
86
+ In the meantime, any questions regarding licensing, and in particular how these two licenses might interact, should be directed to the original model repository: [garage-bAInd's Camel Platypus2 70B](https://huggingface.co/garage-bAInd/Camel-Platypus2-70B).
87
+ <!-- licensing end -->
88
  <!-- README_GPTQ.md-provided-files start -->
89
  ## Provided files and GPTQ parameters
90
 
 
109
 
110
  | Branch | Bits | GS | Act Order | Damp % | GPTQ Dataset | Seq Len | Size | ExLlama | Desc |
111
  | ------ | ---- | -- | --------- | ------ | ------------ | ------- | ---- | ------- | ---- |
112
+ | [main](https://huggingface.co/TheBloke/Camel-Platypus2-70B-GPTQ/tree/main) | 4 | None | Yes | 0.1 | [wikitext](https://huggingface.co/datasets/wikitext/viewer/wikitext-2-v1/test) | 4096 | 35.33 GB | Yes | 4-bit, with Act Order. No group size, to lower VRAM requirements. |
113
+ | [gptq-4bit-32g-actorder_True](https://huggingface.co/TheBloke/Camel-Platypus2-70B-GPTQ/tree/gptq-4bit-32g-actorder_True) | 4 | 32 | Yes | 0.1 | [wikitext](https://huggingface.co/datasets/wikitext/viewer/wikitext-2-v1/test) | 4096 | 40.66 GB | Yes | 4-bit, with Act Order and group size 32g. Gives highest possible inference quality, with maximum VRAM usage. |
114
+ | [gptq-4bit-64g-actorder_True](https://huggingface.co/TheBloke/Camel-Platypus2-70B-GPTQ/tree/gptq-4bit-64g-actorder_True) | 4 | 64 | Yes | 0.1 | [wikitext](https://huggingface.co/datasets/wikitext/viewer/wikitext-2-v1/test) | 4096 | 37.99 GB | Yes | 4-bit, with Act Order and group size 64g. Uses less VRAM than 32g, but with slightly lower accuracy. |
115
+ | [gptq-4bit-128g-actorder_True](https://huggingface.co/TheBloke/Camel-Platypus2-70B-GPTQ/tree/gptq-4bit-128g-actorder_True) | 4 | 128 | Yes | 0.1 | [wikitext](https://huggingface.co/datasets/wikitext/viewer/wikitext-2-v1/test) | 4096 | 36.65 GB | Yes | 4-bit, with Act Order and group size 128g. Uses even less VRAM than 64g, but with slightly lower accuracy. |
116
  | [gptq-3bit--1g-actorder_True](https://huggingface.co/TheBloke/Camel-Platypus2-70B-GPTQ/tree/gptq-3bit--1g-actorder_True) | 3 | None | Yes | 0.1 | [wikitext](https://huggingface.co/datasets/wikitext/viewer/wikitext-2-v1/test) | 4096 | 26.77 GB | No | 3-bit, with Act Order and no group size. Lowest possible VRAM requirements. May be lower quality than 3-bit 128g. |
117
+ | [gptq-3bit-128g-actorder_True](https://huggingface.co/TheBloke/Camel-Platypus2-70B-GPTQ/tree/gptq-3bit-128g-actorder_True) | 3 | 128 | Yes | 0.1 | [wikitext](https://huggingface.co/datasets/wikitext/viewer/wikitext-2-v1/test) | 4096 | 28.03 GB | No | 3-bit, with group size 128g and act-order. Higher quality than 128g-False. |
118
 
119
  <!-- README_GPTQ.md-provided-files end -->
120
 
121
  <!-- README_GPTQ.md-download-from-branches start -->
122
  ## How to download from branches
123
 
124
+ - In text-generation-webui, you can add `:branch` to the end of the download name, eg `TheBloke/Camel-Platypus2-70B-GPTQ:main`
125
  - With Git, you can clone a branch with:
126
  ```
127
+ git clone --single-branch --branch main https://huggingface.co/TheBloke/Camel-Platypus2-70B-GPTQ
128
  ```
129
  - In Python Transformers code, the branch is the `revision` parameter; see below.
130
  <!-- README_GPTQ.md-download-from-branches end -->
 
137
 
138
  1. Click the **Model tab**.
139
  2. Under **Download custom model or LoRA**, enter `TheBloke/Camel-Platypus2-70B-GPTQ`.
140
+ - To download from a specific branch, enter for example `TheBloke/Camel-Platypus2-70B-GPTQ:main`
141
  - see Provided Files above for the list of branches for each option.
142
  3. Click **Download**.
143
  4. The model will start downloading. Once it's finished it will say "Done".
 
185
 
186
  model_name_or_path = "TheBloke/Camel-Platypus2-70B-GPTQ"
187
  # To use a different branch, change revision
188
+ # For example: revision="main"
189
  model = AutoModelForCausalLM.from_pretrained(model_name_or_path,
 
190
  device_map="auto",
191
+ trust_remote_code=False,
192
  revision="main")
193
 
194
  tokenizer = AutoTokenizer.from_pretrained(model_name_or_path, use_fast=True)
 
206
  print("\n\n*** Generate:")
207
 
208
  input_ids = tokenizer(prompt_template, return_tensors='pt').input_ids.cuda()
209
+ output = model.generate(inputs=input_ids, temperature=0.7, do_sample=True, top_p=0.95, top_k=40, max_new_tokens=512)
210
  print(tokenizer.decode(output[0]))
211
 
212
  # Inference can also be done using transformers' pipeline
 
217
  model=model,
218
  tokenizer=tokenizer,
219
  max_new_tokens=512,
220
+ do_sample=True,
221
  temperature=0.7,
222
  top_p=0.95,
223
+ top_k=40,
224
+ repetition_penalty=1.1
225
  )
226
 
227
  print(pipe(prompt_template)[0]['generated_text'])
 
246
 
247
  [TheBloke AI's Discord server](https://discord.gg/theblokeai)
248
 
249
+ ## Thanks, and how to contribute
250
 
251
  Thanks to the [chirper.ai](https://chirper.ai) team!
252
 
253
+ Thanks to Clay from [gpus.llm-utils.org](llm-utils)!
254
+
255
  I've had a lot of people ask if they can contribute. I enjoy providing models and helping people, and would love to be able to spend even more time doing it, as well as expanding into new projects like fine tuning/training.
256
 
257
  If you're able and willing to contribute it will be most gratefully received and will help me to keep providing more models, and to start work on new AI projects.
 
263
 
264
  **Special thanks to**: Aemon Algiz.
265
 
266
+ **Patreon special mentions**: Alicia Loh, Stephen Murray, K, Ajan Kanaga, RoA, Magnesian, Deo Leter, Olakabola, Eugene Pentland, zynix, Deep Realms, Raymond Fosdick, Elijah Stavena, Iucharbius, Erik Bjäreholt, Luis Javier Navarrete Lozano, Nicholas, theTransient, John Detwiler, alfie_i, knownsqashed, Mano Prime, Willem Michiel, Enrico Ros, LangChain4j, OG, Michael Dempsey, Pierre Kircher, Pedro Madruga, James Bentley, Thomas Belote, Luke @flexchar, Leonard Tan, Johann-Peter Hartmann, Illia Dulskyi, Fen Risland, Chadd, S_X, Jeff Scroggin, Ken Nordquist, Sean Connelly, Artur Olbinski, Swaroop Kallakuri, Jack West, Ai Maven, David Ziegler, Russ Johnson, transmissions 11, John Villwock, Alps Aficionado, Clay Pascal, Viktor Bowallius, Subspace Studios, Rainer Wilmers, Trenton Dambrowitz, vamX, Michael Levine, 준교 김, Brandon Frisco, Kalila, Trailburnt, Randy H, Talal Aujan, Nathan Dryer, Vadim, 阿明, ReadyPlayerEmma, Tiffany J. Kim, George Stoitzev, Spencer Kim, Jerry Meng, Gabriel Tamborski, Cory Kujawski, Jeffrey Morgan, Spiking Neurons AB, Edmond Seymore, Alexandros Triantafyllidis, Lone Striker, Cap'n Zoog, Nikolai Manek, danny, ya boyyy, Derek Yates, usrbinkat, Mandus, TL, Nathan LeClaire, subjectnull, Imad Khwaja, webtim, Raven Klaugh, Asp the Wyvern, Gabriel Puliatti, Caitlyn Gatomon, Joseph William Delisle, Jonathan Leane, Luke Pendergrass, SuperWojo, Sebastain Graf, Will Dee, Fred von Graf, Andrey, Dan Guido, Daniel P. Andersen, Nitin Borwankar, Elle, Vitor Caleffi, biorpg, jjj, NimbleBox.ai, Pieter, Matthew Berman, terasurfer, Michael Davis, Alex, Stanislav Ovsiannikov
267
 
268
 
269
  Thank you to all my generous patrons and donaters!