Update README.md

README.md

@@ -4,19 +4,17 @@ language:
 - en
 license: apache-2.0
 base_model: pszemraj/tFINE-850m-24x24-v0.4-flan_aug
-tags:
-- generated_from_trainer
 metrics:
 - rouge
-model-index:
-- name: tFINE-850m-24x24-v0.4-flan_aug-infinity-instruct-7m-T2T_en-1024-v5
-  results: []
+datasets:
+- pszemraj/infinity-instruct-7m-T2T_en
+pipeline_tag: text2text-generation
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 should probably proofread and complete it, then remove this comment. -->
 
-# tFINE-850m-24x24-v0.4-flan_aug-infinity-instruct-7m-T2T_en-1024-v5
+# tFINE-850m-24x24-v0.5-instruct-L1
 
 This model is a fine-tuned version of [pszemraj/tFINE-850m-24x24-v0.4-flan_aug](https://huggingface.co/pszemraj/tFINE-850m-24x24-v0.4-flan_aug) on the pszemraj/infinity-instruct-7m-T2T_en dataset.
 It achieves the following results on the evaluation set:
@@ -28,6 +26,26 @@ It achieves the following results on the evaluation set:
 - Gen Len: 441.475
 - Num Input Tokens Seen: 435513684
 
+## usage
+
+```py
+from transformers import pipeline
+
+pipe = pipeline(
+    "text2text-generation", model="pszemraj/tFINE-850m-24x24-v0.5-instruct-L1"
+)
+prompt = "write a python script to download a file from a url and save as a local file using requests. explain how it works"
+res = pipe(
+    prompt,
+    max_new_tokens=192,
+    top_k=4,
+    penalty_alpha=0.6,
+    renormalize_logits=True,
+    no_repeat_ngram_size=5,
+)
+print(res[0]["generated_text"])
+```
+
 ## Quick eval
 
 Quick eval for:	`pszemraj/tFINE-850m-24x24-v0.5-instruct-L1`
@@ -49,36 +67,3 @@ hf (pretrained=pszemraj/tFINE-850m-24x24-v0.5-instruct-L1,trust_remote_code=True
 |tinyMMLU     |      0|none            |     0|acc_norm   |↑  |0.3021|±  |   N/A|
 |winogrande   |      1|none            |     0|acc        |↑  |0.4925|±  |0.0141|
 
-## Training procedure
-
-### Training hyperparameters
-
-The following hyperparameters were used during training:
-- learning_rate: 3e-05
-- train_batch_size: 4
-- eval_batch_size: 4
-- seed: 776444
-- gradient_accumulation_steps: 32
-- total_train_batch_size: 128
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: constant_with_warmup
-- lr_scheduler_warmup_ratio: 0.05
-- num_epochs: 1.0
-
-### Training results
-
-| Training Loss | Epoch  | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len | Input Tokens Seen |
-|:-------------:|:------:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-----------------:|
-| 1.8808        | 0.0807 | 1000  | 1.7883          | 24.1946 | 12.2099 | 20.4185 | 22.251    | 636.465 | 35147692          |
-| 1.6545        | 0.1613 | 2000  | 1.5985          | 28.9492 | 15.3233 | 23.871  | 26.9919   | 577.04  | 70510224          |
-| 1.5522        | 0.2420 | 3000  | 1.4907          | 30.4033 | 16.1354 | 24.7244 | 28.5037   | 537.77  | 105707144         |
-| 1.5059        | 0.3227 | 4000  | 1.4204          | 34.0294 | 19.2608 | 27.9322 | 32.3166   | 522.495 | 140722844         |
-| 1.4346        | 0.4034 | 5000  | 1.3636          | 34.4104 | 19.4149 | 28.1022 | 32.7299   | 494.68  | 175639924         |
-| 1.3912        | 0.4840 | 6000  | 1.3159          | 36.5059 | 21.2447 | 30.116  | 34.7303   | 469.885 | 210409328         |
-| 1.3148        | 0.5647 | 7000  | 1.2807          | 37.0123 | 21.3666 | 30.11   | 35.0891   | 458.28  | 245601908         |
-| 1.2859        | 0.6454 | 8000  | 1.2492          | 37.05   | 21.0468 | 29.7988 | 35.1882   | 452.495 | 280866724         |
-| 1.298         | 0.7260 | 9000  | 1.2211          | 36.6966 | 20.8189 | 29.7115 | 34.7528   | 464.37  | 316042068         |
-| 1.2834        | 0.8067 | 10000 | 1.1979          | 37.7181 | 20.9926 | 30.3857 | 35.8681   | 446.26  | 351056548         |
-| 1.2577        | 0.8874 | 11000 | 1.1752          | 39.3539 | 23.0123 | 31.9005 | 37.4941   | 424.445 | 386471860         |
-| 1.193         | 0.9680 | 12000 | 1.1526          | 40.1804 | 23.1008 | 32.3484 | 38.2103   | 422.225 | 421585440         |
-