Update for Transformers GPTQ support

README.md

@@ -4,17 +4,20 @@ license: other
 ---
 
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-<div style="width: 100%;">
-    <img src="https://i.imgur.com/EBdldam.jpg" alt="TheBlokeAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
+<!-- 200823 -->
+<div style="width: auto; margin-left: auto; margin-right: auto">
+<img src="https://i.imgur.com/EBdldam.jpg" alt="TheBlokeAI" style="width: 100%; min-width: 400px; display: block; margin: auto;">
 </div>
 <div style="display: flex; justify-content: space-between; width: 100%;">
     <div style="display: flex; flex-direction: column; align-items: flex-start;">
-        <p><a href="https://discord.gg/theblokeai">Chat & support: my new Discord server</a></p>
+        <p style="margin-top: 0.5em; margin-bottom: 0em;"><a href="https://discord.gg/theblokeai">Chat & support: TheBloke's Discord server</a></p>
     </div>
     <div style="display: flex; flex-direction: column; align-items: flex-end;">
-        <p><a href="https://www.patreon.com/TheBlokeAI">Want to contribute? TheBloke's Patreon page</a></p>
+        <p style="margin-top: 0.5em; margin-bottom: 0em;"><a href="https://www.patreon.com/TheBlokeAI">Want to contribute? TheBloke's Patreon page</a></p>
     </div>
 </div>
+<div style="text-align:center; margin-top: 0em; margin-bottom: 0em"><p style="margin-top: 0.25em; margin-bottom: 0em;">TheBloke's LLM work is generously supported by a grant from <a href="https://a16z.com">andreessen horowitz (a16z)</a></p></div>
+<hr style="margin-top: 1.0em; margin-bottom: 1.0em;">
 <!-- header end -->
 
 # OpenAccess AI Collective's Manticore 13B GPTQ
@@ -146,6 +149,7 @@ It was created with group_size 128 to increase inference accuracy, but without -
   * Parameters: Groupsize = 128. Act Order / desc_act = False.
 
 <!-- footer start -->
+<!-- 200823 -->
 ## Discord
 
 For further support, and discussions on these models and AI in general, join us at:
@@ -165,12 +169,15 @@ Donaters will get priority support on any and all AI/LLM/model questions and req
 * Patreon: https://patreon.com/TheBlokeAI
 * Ko-Fi: https://ko-fi.com/TheBlokeAI
 
-**Special thanks to**: Luke from CarbonQuill, Aemon Algiz, Dmitriy Samsonov.
+**Special thanks to**: Aemon Algiz.
+
+**Patreon special mentions**: Sam, theTransient, Jonathan Leane, Steven Wood, webtim, Johann-Peter Hartmann, Geoffrey Montalvo, Gabriel Tamborski, Willem Michiel, John Villwock, Derek Yates, Mesiah Bishop, Eugene Pentland, Pieter, Chadd, Stephen Murray, Daniel P. Andersen, terasurfer, Brandon Frisco, Thomas Belote, Sid, Nathan LeClaire, Magnesian, Alps Aficionado, Stanislav Ovsiannikov, Alex, Joseph William Delisle, Nikolai Manek, Michael Davis, Junyu Yang, K, J, Spencer Kim, Stefan Sabev, Olusegun Samson, transmissions 11, Michael Levine, Cory Kujawski, Rainer Wilmers, zynix, Kalila, Luke @flexchar, Ajan Kanaga, Mandus, vamX, Ai Maven, Mano Prime, Matthew Berman, subjectnull, Vitor Caleffi, Clay Pascal, biorpg, alfie_i, 阿明, Jeffrey Morgan, ya boyyy, Raymond Fosdick, knownsqashed, Olakabola, Leonard Tan, ReadyPlayerEmma, Enrico Ros, Dave, Talal Aujan, Illia Dulskyi, Sean Connelly, senxiiz, Artur Olbinski, Elle, Raven Klaugh, Fen Risland, Deep Realms, Imad Khwaja, Fred von Graf, Will Dee, usrbinkat, SuperWojo, Alexandros Triantafyllidis, Swaroop Kallakuri, Dan Guido, John Detwiler, Pedro Madruga, Iucharbius, Viktor Bowallius, Asp the Wyvern, Edmond Seymore, Trenton Dambrowitz, Space Cruiser, Spiking Neurons AB, Pyrater, LangChain4j, Tony Hughes, Kacper Wikieł, Rishabh Srivastava, David Ziegler, Luke Pendergrass, Andrey, Gabriel Puliatti, Lone Striker, Sebastain Graf, Pierre Kircher, Randy H, NimbleBox.ai, Vadim, danny, Deo Leter
 
-**Patreon special mentions**: zynix , ya boyyy, Trenton Dambrowitz, Imad Khwaja, Alps Aficionado, chris gileta, John Detwiler, Willem Michiel, RoA, Mano Prime, Rainer Wilmers, Fred von Graf, Matthew Berman, Ghost , Nathan LeClaire, Iucharbius , Ai Maven, Illia Dulskyi, Joseph William Delisle, Space Cruiser, Lone Striker, Karl Bernard, Eugene Pentland, Greatston Gnanesh, Jonathan Leane, Randy H, Pierre Kircher, Willian Hasse, Stephen Murray, Alex , terasurfer , Edmond Seymore, Oscar Rangel, Luke Pendergrass, Asp the Wyvern, Junyu Yang, David Flickinger, Luke, Spiking Neurons AB, subjectnull, Pyrater, Nikolai Manek, senxiiz, Ajan Kanaga, Johann-Peter Hartmann, Artur Olbinski, Kevin Schuppel, Derek Yates, Kalila, K, Talal Aujan, Khalefa Al-Ahmad, Gabriel Puliatti, John Villwock, WelcomeToTheClub, Daniel P. Andersen, Preetika Verma, Deep Realms, Fen Risland, trip7s trip, webtim, Sean Connelly, Michael Levine, Chris McCloskey, biorpg, vamX, Viktor Bowallius, Cory Kujawski.
 
 Thank you to all my generous patrons and donaters!
 
+And thank you again to a16z for their generous grant.
+
 <!-- footer end -->
 
 # Original model card: Kaio Ken's SuperHOT 8K
@@ -246,8 +253,8 @@ Try out the model in HF Spaces. The demo uses a quantized GGML version of the mo
 
 ## Build
 
-Manticore was built with [Axolotl](https://github.com/OpenAccess-AI-Collective/axolotl) on 8xA100 80GB 
- - Preview Release: 3 epochs taking approximately 24 hours. 
+Manticore was built with [Axolotl](https://github.com/OpenAccess-AI-Collective/axolotl) on 8xA100 80GB
+ - Preview Release: 3 epochs taking approximately 24 hours.
  - The configuration to duplicate this build is provided in this repo's [/config folder](https://huggingface.co/openaccess-ai-collective/manticore-13b/tree/main/configs).
 
 ## Bias, Risks, and Limitations
@@ -265,20 +272,20 @@ Here’s an example of how you can use memoization to efficiently calculate the
 def fib(n):
  # Memoize the last calculated Fibonacci number for each index
  cache = {}
- 
+
  def fib_memoized(n):
  if n not in cache:
  cache[n] = [0, 1]
  else:
  return cache[n][-1], cache[n][-2]
- 
+
  # Recursive helper function to calculate the Fibonacci sequence up to a given index
  def fib_helper(n):
  if n == 0 or n == 1:
  return 0, 1
  else:
  return fib_helper(n - 1) + fib_helper(n - 2)
- 
+
 # Calculate the first n numbers of the Fibonacci sequence using memoization
  def fib_memoized_seq(n):
  if n == 0 or n == 1:
@@ -287,7 +294,7 @@ def fib(n):
  result = fib_helper(n - 1) + fib_helper(n - 2)
  cache[n] = [result]
  return result, cache[n][-1], cache[n][-2]
- 
+
  # Example usage
  for i in range(len(fib_memoized_seq(3))):
  print(fib_memoized_seq(3)[i])
@@ -297,18 +304,18 @@ In this implementation, we use a cache dictionary to memoize the last calculated
 ````
 
 ```
-USER: Finish the joke, a mechanic and a car salesman walk into a bar...  
+USER: Finish the joke, a mechanic and a car salesman walk into a bar...
 ASSISTANT: … and when they get up to leave, they realize that they’ve left their keys in their cars. The mechanic says “I know how to fix this” and opens his toolbox to grab something. Then he stops and looks at the salesman. He says “You drive a Toyota, right?” The salesman nods. The mechanic then takes out a tiny screwdriver from his toolbox and starts working on the lock of the car door. The salesman is amazed and asks how he knew that. The mechanic replies “I can tell by the way you parked your car.”
 ```
 
 ```
 USER: Describe how a tsunami would affect the residents of Denver Colorado
-ASSISTANT: The impact of a tsunami in Denver, Colorado would likely be minimal. As there are no coastal areas or bodies of water nearby, a tsunami generated from an earthquake or volcanic activity elsewhere in the world would have little effect on the city and its residents. Even if a large tsunami were to hit the coastline of California or Mexico, the distance between Denver and these locations means that any impacts on the city itself would be minimal. 
+ASSISTANT: The impact of a tsunami in Denver, Colorado would likely be minimal. As there are no coastal areas or bodies of water nearby, a tsunami generated from an earthquake or volcanic activity elsewhere in the world would have little effect on the city and its residents. Even if a large tsunami were to hit the coastline of California or Mexico, the distance between Denver and these locations means that any impacts on the city itself would be minimal.
 ```
 
 ```
 USER: If you could do one thing right now, what would it be?
-ASSISTANT: I’d hug my loved ones a little tighter today and tell them how much they mean to me. 
+ASSISTANT: I’d hug my loved ones a little tighter today and tell them how much they mean to me.
 USER: And who are your loved ones?
 ASSISTANT: My closest friends and family members.
 USER: What are their names?

config.json

@@ -1,29 +1,39 @@
 {
-    "_name_or_path": "/workspace/superhot_process/manticore-13b/source",
-    "architectures": [
-        "LlamaForCausalLM"
-    ],
-    "bos_token_id": 1,
-    "eos_token_id": 2,
-    "hidden_act": "silu",
-    "hidden_size": 5120,
-    "initializer_range": 0.02,
-    "intermediate_size": 13824,
-    "max_position_embeddings": 8192,
-    "max_sequence_length": 2048,
-    "model_type": "llama",
-    "num_attention_heads": 40,
-    "num_hidden_layers": 40,
-    "pad_token_id": 0,
-    "rms_norm_eps": 1e-06,
-    "tie_word_embeddings": false,
-    "torch_dtype": "float16",
-    "transformers_version": "4.30.0.dev0",
-    "use_cache": true,
-    "vocab_size": 32000,
-    "auto_map": {
-        "AutoModel": "modelling_llama.LlamaModel",
-        "AutoModelForCausalLM": "modelling_llama.LlamaForCausalLM",
-        "AutoModelForSequenceClassification": "modelling_llama.LlamaForSequenceClassification"
-    }
+  "_name_or_path": "/workspace/superhot_process/manticore-13b/source",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 5120,
+  "initializer_range": 0.02,
+  "intermediate_size": 13824,
+  "max_position_embeddings": 8192,
+  "max_sequence_length": 2048,
+  "model_type": "llama",
+  "num_attention_heads": 40,
+  "num_hidden_layers": 40,
+  "pad_token_id": 0,
+  "rms_norm_eps": 1e-06,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float16",
+  "transformers_version": "4.30.0.dev0",
+  "use_cache": true,
+  "vocab_size": 32000,
+  "auto_map": {
+    "AutoModel": "modelling_llama.LlamaModel",
+    "AutoModelForCausalLM": "modelling_llama.LlamaForCausalLM",
+    "AutoModelForSequenceClassification": "modelling_llama.LlamaForSequenceClassification"
+  },
+  "quantization_config": {
+    "bits": 4,
+    "group_size": 128,
+    "damp_percent": 0.01,
+    "desc_act": false,
+    "sym": true,
+    "true_sequential": true,
+    "model_file_base_name": "model",
+    "quant_method": "gptq"
+  }
 }

manticore-13b-superhot-8k-GPTQ-4bit-128g.no-act.order.safetensors → model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:3e6358e48ff549d0403cfa0c159278630d6d228fabd910413d1520c434d2cfee
-size 7454797160
+oid sha256:a0077198bcf20e8ebe7e6790d8dbcbd86288b74fe9fca1217d6a35f51b8b5c73
+size 7454797216

quantize_config.json

@@ -1,8 +1,9 @@
 {
-    "bits": 4,
-    "group_size": 128,
-    "damp_percent": 0.01,
-    "desc_act": false,
-    "sym": true,
-    "true_sequential": true
+  "bits": 4,
+  "group_size": 128,
+  "damp_percent": 0.01,
+  "desc_act": false,
+  "sym": true,
+  "true_sequential": true,
+  "model_file_base_name": "model"
 }