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README.md

@@ -1,20 +1,59 @@
 ---
 license: llama2
+language:
+- en
+pipeline_tag: conversational
 ---
-Another EXL2 version of AlpinDale's https://huggingface.co/alpindale/goliath-120b this one being at 2.64BPW.
+# Goliath 120B
 
-[2.37BPW](https://huggingface.co/LavaPlanet/Goliath120B-exl2-2.37bpw)
+An auto-regressive causal LM created by combining 2x finetuned [Llama-2 70B](https://huggingface.co/meta-llama/llama-2-70b-hf) into one.
 
-Pippa llama2 Chat was used as the calibration dataset.
+Please check out the quantized formats provided by [@TheBloke](https:///huggingface.co/TheBloke) and [@Panchovix](https://huggingface.co/Panchovix):
 
-Can be run on two RTX 3090s w/ 24GB vram each.
+- [GGUF](https://huggingface.co/TheBloke/goliath-120b-GGUF) (llama.cpp)
+- [GPTQ](https://huggingface.co/TheBloke/goliath-120b-GPTQ) (KoboldAI, TGW, Aphrodite)
+- [AWQ](https://huggingface.co/TheBloke/goliath-120b-AWQ) (TGW, Aphrodite, vLLM)
+- [Exllamav2](https://huggingface.co/Panchovix/goliath-120b-exl2) (TGW, KoboldAI)
+
+# Prompting Format
+
+Both Vicuna and Alpaca will work, but due the initial and final layers belonging primarily to Xwin, I expect Vicuna to work the best.
+
+# Merge process
+
+The models used in the merge are [Xwin](https://huggingface.co/Xwin-LM/Xwin-LM-70B-V0.1) and [Euryale](https://huggingface.co/Sao10K/Euryale-1.3-L2-70B).
+
+The layer ranges used are as follows:
 
-Assuming Windows overhead, the following figures should be more or less close enough for estimation of your own use. 
 ```yaml
-2.64BPW @ 4096 ctx
-  Empty Ctx
-    GPU Split:18/24
-    GPU1: 19.8/24
-    GPU2: 21.9/24
-    10~ tk/s
-```
+- range 0, 16
+  Xwin
+- range 8, 24
+  Euryale
+- range 17, 32
+  Xwin
+- range 25, 40
+  Euryale
+- range 33, 48
+  Xwin
+- range 41, 56
+  Euryale
+- range 49, 64
+  Xwin
+- range 57, 72
+  Euryale
+- range 65, 80
+  Xwin
+```
+
+# Screenshots
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/635567189c72a7e742f1419c/Cat8_Rimaz6Ni7YhQiiGB.png)
+
+# Benchmarks
+Coming soon.
+
+# Acknowledgements
+Credits goes to [@chargoddard](https://huggingface.co/chargoddard) for developing the framework used to merge the model - [mergekit](https://github.com/cg123/mergekit).
+
+Special thanks to [@Undi95](https://huggingface.co/Undi95) for helping with the merge ratios.

config.json

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+{
+  "_name_or_path": "alpindale/goliath-120b",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 8192,
+  "initializer_range": 0.02,
+  "intermediate_size": 28672,
+  "max_position_embeddings": 4096,
+  "model_type": "llama",
+  "num_attention_heads": 64,
+  "num_hidden_layers": 137,
+  "num_key_value_heads": 8,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 10000.0,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float16",
+  "transformers_version": "4.35.0",
+  "use_cache": true,
+  "vocab_size": 32000
+}

model.safetensors.index.json

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