Upload folder using huggingface_hub (#2)

- e41180369ff8d190dc9f235a3c33ad50a1a791bed3f2368019b1949b69d7dd5e (dac86450b89e56daedf03be16a0aece8fde198c9)
- ebd69bf97e68101fb3737a9c38582beec9ab0a8fff6c981d25c552cb68c3133c (54ae27c8d6c2e537ec56815bff76beffcd7fe026)

README.md

@@ -1,5 +1,4 @@
 ---
-library_name: pruna-engine
 thumbnail: "https://assets-global.website-files.com/646b351987a8d8ce158d1940/64ec9e96b4334c0e1ac41504_Logo%20with%20white%20text.svg"
 metrics:
 - memory_disk
@@ -8,6 +7,8 @@ metrics:
 - inference_throughput
 - inference_CO2_emissions
 - inference_energy_consumption
+tags:
+- pruna-ai
 ---
 <!-- header start -->
 <!-- 200823 -->
@@ -33,7 +34,7 @@ metrics:
 
 ## Results
 
-Detailed efficiency metrics coming soon!
+![image info](./plots.png)
 
 **Frequently Asked Questions**
 - ***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:
    from transformers import AutoModelForCausalLM, AutoTokenizer
 
     model = AutoModelForCausalLM.from_pretrained("PrunaAI/meta-math-MetaMath-Mistral-7B-bnb-4bit-smashed",
-                                                 trust_remote_code=True)
+                                                 trust_remote_code=True, device_map='auto')
     tokenizer = AutoTokenizer.from_pretrained("meta-math/MetaMath-Mistral-7B")
     
     input_ids = tokenizer("What is the color of prunes?,", return_tensors='pt').to(model.device)["input_ids"]

config.json

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "/tmp/tmpyhtabq1q",
+  "_name_or_path": "/tmp/tmp8cmf7uza",
   "architectures": [
     "MistralForCausalLM"
   ],
@@ -18,7 +18,7 @@
   "quantization_config": {
     "bnb_4bit_compute_dtype": "bfloat16",
     "bnb_4bit_quant_type": "fp4",
-    "bnb_4bit_use_double_quant": true,
+    "bnb_4bit_use_double_quant": false,
     "llm_int8_enable_fp32_cpu_offload": false,
     "llm_int8_has_fp16_weight": false,
     "llm_int8_skip_modules": [

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:e3c4fe0cb1ff85b75e7b8b198db3da14ea148612bdd3b2ec5e9f52d5824b0198
-size 4125704005
+oid sha256:b427b1449b3b6a0b63b5491583fa4380f897a11f91662f36d33bc0bf9f99f08c
+size 4450853880

smash_config.json

@@ -8,7 +8,7 @@
         "compilers": "None",
         "task": "text_text_generation",
         "device": "cuda",
-        "cache_dir": "/ceph/hdd/staff/charpent/.cache/models4hr3z1d2",
+        "cache_dir": "/ceph/hdd/staff/charpent/.cache/models7xc5pi2s",
         "batch_size": 1,
         "model_name": "meta-math/MetaMath-Mistral-7B",
         "pruning_ratio": 0.0,