9fcbe6613864ad11697e03b879ad2c37a366039f7cdd27017bfa03d82a051d91

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/WizardLM-WizardCoder-3B-V1.0-bnb-4bit-smashed",
-                                                 trust_remote_code=True)
+                                                 trust_remote_code=True, device_map='auto')
     tokenizer = AutoTokenizer.from_pretrained("WizardLM/WizardCoder-3B-V1.0")
     
     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/tmpvo_oyjzs",
+  "_name_or_path": "/tmp/tmp_mlfw6rl",
   "activation_function": "gelu_pytorch_tanh",
   "architectures": [
     "GPTBigCodeForCausalLM"
@@ -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 sha256:5babba4d9e92a56614802b09589d91163f73756a76eb8e4ccdec7e7da7ff2f20
-size 1811600454
+oid sha256:b7fe584d59d6ccd25f7f792864fd0a6ac69b04d687aa4cfc0b80438a3a8a539c
+size 1945738592

smash_config.json

@@ -8,7 +8,7 @@
         "compilers": "None",
         "task": "text_text_generation",
         "device": "cuda",
-        "cache_dir": "/ceph/hdd/staff/charpent/.cache/modelsdxv16d8t",
+        "cache_dir": "/ceph/hdd/staff/charpent/.cache/models0ajjpv51",
         "batch_size": 1,
         "model_name": "WizardLM/WizardCoder-3B-V1.0",
         "pruning_ratio": 0.0,