Add bfloat16 version and optimum_quanto_qfloat8 version.

README.md

@@ -1,3 +1,12 @@
 ---
 license: apache-2.0
 ---
+
+# T5-XXL Encoder
+
+This repo contains copies of the T5-XXL encoder in various quantization formats. The models in this repo are intended for use in [InvokeAI](https://github.com/invoke-ai/InvokeAI).
+
+Contents:
+- `bfloat16/` - T5-XXL encoder cast to bfloat16. Copied from [here](https://huggingface.co/black-forest-labs/FLUX.1-schnell/tree/741f7c3ce8b383c54771c7003378a50191e9efe9/text_encoder_2).
+- `optimum_quanto_qfloat8` - T5-XXL encoder quantized using [optimum-quanto](https://github.com/huggingface/optimum-quanto) qfloat8 quantization.
+

bfloat16/text_encoder_2/config.json

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+{
+  "_name_or_path": "google/t5-v1_1-xxl",
+  "architectures": [
+    "T5EncoderModel"
+  ],
+  "classifier_dropout": 0.0,
+  "d_ff": 10240,
+  "d_kv": 64,
+  "d_model": 4096,
+  "decoder_start_token_id": 0,
+  "dense_act_fn": "gelu_new",
+  "dropout_rate": 0.1,
+  "eos_token_id": 1,
+  "feed_forward_proj": "gated-gelu",
+  "initializer_factor": 1.0,
+  "is_encoder_decoder": true,
+  "is_gated_act": true,
+  "layer_norm_epsilon": 1e-06,
+  "model_type": "t5",
+  "num_decoder_layers": 24,
+  "num_heads": 64,
+  "num_layers": 24,
+  "output_past": true,
+  "pad_token_id": 0,
+  "relative_attention_max_distance": 128,
+  "relative_attention_num_buckets": 32,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.43.3",
+  "use_cache": true,
+  "vocab_size": 32128
+}

bfloat16/text_encoder_2/model-00001-of-00002.safetensors

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optimum_quanto_qfloat8/tokenizer_2/special_tokens_map.json

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optimum_quanto_qfloat8/tokenizer_2/spiece.model

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+}