small changes & meta-llama_Llama-3.2-1B_4e20de362430cd3b72f300e6b0f18e50e7166e08.logits.safetensors

compress_weights.bash

@@ -6,12 +6,18 @@
 LEVEL=-4
 #LEVEL=-9
 #LEVEL=--adapt=min=1,max=22
+PV="pv -cpteabm $((60*60*24))"
+#PV="pv -cpteab"
 
 model_id="$1"
 revision="$2"
 repo_url=https://huggingface.co/"$model_id"
 clonepath="$(basename "$repo_url")"
 cachepath="${HOME}/.cache/huggingface/hub/models--${model_id//\//--}/blobs"
+if ! [ -e ${HOME}/.cache/huggingface/token ]
+then
+	huggingface-cli login || exit -1
+fi
 HF_TOKEN="$(<${HOME}/.cache/huggingface/token)"
 GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/"$1" "$clonepath"
 mkdir -p "$cachepath"
@@ -28,11 +34,11 @@ do
 		zstd -l "$outfile" && { echo "$file" 1>&3; continue; }
 		echo
 		echo "# Recompressing $file #"
-		echo
 	fi
-	curl -s -L -H "Authorization: Bearer $HF_TOKEN" "$file_url" | pv -cpteabm $((60*60*24)) -s "$size" -N "$file" | zstd -q --no-progress --force --size-hint="$size" --stream-size="$size" --ultra --long=31 --memory=2048MB --threads=1024 "$LEVEL" | pv -cpteabm $((60*60*24)) -s "$((size * 100/129))" -N "$blobname".zst > "$outfile"
+	echo
+	{ curl -s -L -H "Authorization: Bearer $HF_TOKEN" "$file_url" || exit -1; } | $PV -s "$size" -N "$file" | zstd -q --no-progress --force --size-hint="$size" --stream-size="$size" --ultra --long=31 --memory=2048MB --threads=1024 "$LEVEL" | $PV -s "$((size * 100/129))" -N "$blobname".zst > "$outfile"
 	zstd -l "$outfile"
 	echo
 	echo
 	echo "$file" 1>&3
-done 3>&1 1>&2 | pv -lcpteabm $((60*60*24)) -s "$filecount" -N "$clonepath"
+done 3>&1 1>&2 | $PV -l -s "$filecount" -N "$clonepath"

meta-llama_Llama-3.2-1B_4e20de362430cd3b72f300e6b0f18e50e7166e08.logits.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:f06331e234681c98d34d740644c47c5a5d615ab262ecfdc11da914b96779d47c
-size 15543560
+oid sha256:cf91a8326bf10191c5159b95380774e690ea7086792cb4f1e8b735c9e30dbcd1
+size 12049921944

run_test.py

@@ -28,15 +28,15 @@ if config.model_type == 'deepseek_v3':
 model = Model.from_pretrained(model_id, revision=revision, trust_remote_code=True, torch_dtype=torch.float64, use_safetensors=True)
 if config.model_type == 'deepseek_v3':
     model._supports_cache_class = False
-model = accelerate.cpu_offload(model, 'cuda:0', offload_buffers=True)
+#model = accelerate.cpu_offload(model, 'cuda:0', offload_buffers=True)
 
-pipe = transformers.pipeline('text-generation', model=model, config=config, tokenizer=tokenizer)
+pipe = transformers.pipeline('text-generation', model=model, config=config, tokenizer=tokenizer, device='cpu')
 
 tensors = {}
 def store_tensor(descr, tensor):
-    tensors[descr] = tensor.cpu().detach().contiguous()
+    tensors[descr] = tensor.cpu().detach().contiguous().clone()
 
-IDX = 0
+IDX = 0 # IDX is unused
 module_names = {mod:name for name, mod in pipe.model.named_modules()}
 tensors = {}
 def hook(module, inputs, outputs):