9be4c360fa3e2a9a27d795b516b4294659b773238c813431aa7d6c5de7fe85ce

README.md

@@ -34,7 +34,7 @@ tags:
 
 ## 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.
@@ -61,7 +61,7 @@ You can run the smashed model with these steps:
    from transformers import AutoModelForCausalLM, AutoTokenizer
 
     model = AutoModelForCausalLM.from_pretrained("PrunaAI/facebook-galactica-1.3b-bnb-4bit-smashed",
-                                                 trust_remote_code=True)
+                                                 trust_remote_code=True, device_map='auto')
     tokenizer = AutoTokenizer.from_pretrained("facebook/galactica-1.3b")
     
     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/tmpkbd2s4_3",
+  "_name_or_path": "/tmp/tmpah1ntay5",
   "_remove_final_layer_norm": false,
   "activation_dropout": 0.0,
   "activation_function": "gelu",
@@ -26,7 +26,7 @@
   "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 sha256:746cceed5f4842fe3c88ccaaf887f8c116cd46878a061ca438d0e27712df91e4
-size 837947656
+oid sha256:0fa71748f33ac1fbf6828ad100d7155dd13774d57bd120cd27c1799d15550183
+size 894080584

smash_config.json

@@ -8,7 +8,7 @@
         "compilers": "None",
         "task": "text_text_generation",
         "device": "cuda",
-        "cache_dir": "/ceph/hdd/staff/charpent/.cache/models26mk9kuj",
+        "cache_dir": "/ceph/hdd/staff/charpent/.cache/models6og_z66a",
         "batch_size": 1,
         "model_name": "facebook/galactica-1.3b",
         "pruning_ratio": 0.0,