Upload new GPTQs with varied parameters

README.md

@@ -1,6 +1,25 @@
 ---
+datasets:
+- ehartford/WizardLM_alpaca_evol_instruct_70k_unfiltered
+- QingyiSi/Alpaca-CoT
+- teknium/GPTeacher-General-Instruct
+- metaeval/ScienceQA_text_only
+- hellaswag
+- openai/summarize_from_feedback
+- riddle_sense
+- gsm8k
+- camel-ai/math
+- camel-ai/biology
+- camel-ai/physics
+- camel-ai/chemistry
+- winglian/evals
 inference: false
 license: other
+model_type: llama
+tags:
+- OpenAccess AI Collective
+- MPT
+- axolotl
 ---
 
 <!-- header start -->
@@ -38,7 +57,6 @@ A chat between a curious user and an artificial intelligence assistant. The assi
 
 USER: {prompt}
 ASSISTANT:
-
 ```
 
 ## Provided files
@@ -51,8 +69,8 @@ Each separate quant is in a different branch.  See below for instructions on fet
 | ------ | ---- | ---------- | -------------------- | --------- | ------------------- | --------- | ----------- |
 | main | 4 | 128 | False | 7.45 GB | True | GPTQ-for-LLaMa | Most compatible option. Good inference speed in AutoGPTQ and GPTQ-for-LLaMa. Lower inference quality than other options. |
 | gptq-4bit-32g-actorder_True | 4 | 32 | True | 8.00 GB | True | AutoGPTQ | 4-bit, with Act Order and group size. 32g gives highest possible inference quality, with maximum VRAM usage. Poor AutoGPTQ CUDA speed. |
-| gptq-4bit-64g-actorder_True | 4 | 64 | True | 7.51 GB | True | AutoGPTQ | 4-bit, with Act Order and group size. 64g uses less VRAM, but with slightly lower accuracy. Poor AutoGPTQ CUDA speed. |
-| gptq-4bit-128g-actorder_True | 4 | 128 | True | 7.26 GB | True | AutoGPTQ | 4-bit, with Act Order androup size. 128g uses even less VRAM, but with slightly lower accuracy. Poor AutoGPTQ CUDA speed. |
+| gptq-4bit-64g-actorder_True | 4 | 64 | True | 7.51 GB | True | AutoGPTQ | 4-bit, with Act Order and group size. 64g uses less VRAM than 32g, but with slightly lower accuracy. Poor AutoGPTQ CUDA speed. |
+| gptq-4bit-128g-actorder_True | 4 | 128 | True | 7.26 GB | True | AutoGPTQ | 4-bit, with Act Order and group size. 128g uses even less VRAM, but with slightly lower accuracy. Poor AutoGPTQ CUDA speed. |
 | gptq-8bit--1g-actorder_True | 8 | None | True | 13.36 GB | False | AutoGPTQ | 8-bit, with Act Order. No group size, to lower VRAM requirements and to improve AutoGPTQ speed. |
 | gptq-8bit-128g-actorder_False | 8 | 128 | False | 13.65 GB | False | AutoGPTQ | 8-bit, with group size 128g for higher inference quality and without Act Order to improve AutoGPTQ speed. |
 
@@ -128,7 +146,6 @@ prompt_template=f'''A chat between a curious user and an artificial intelligence
 
 USER: {prompt}
 ASSISTANT:
-
 '''
 
 print("\n\n*** Generate:")