Text Classification
Transformers
Safetensors
llama
trl
reward-trainer
Generated from Trainer
text-embeddings-inference
Instructions to use smohammadi/tinyllama_rm_sentiment_1b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use smohammadi/tinyllama_rm_sentiment_1b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="smohammadi/tinyllama_rm_sentiment_1b")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("smohammadi/tinyllama_rm_sentiment_1b") model = AutoModelForSequenceClassification.from_pretrained("smohammadi/tinyllama_rm_sentiment_1b") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -19,7 +19,7 @@ should probably proofread and complete it, then remove this comment. -->
|
|
| 19 |
|
| 20 |
# tinyllama_rm_sentiment_1b
|
| 21 |
|
| 22 |
-
This model is a fine-tuned version of [TinyLlama/TinyLlama_v1.1](https://huggingface.co/TinyLlama/TinyLlama_v1.1) on
|
| 23 |
It achieves the following results on the evaluation set:
|
| 24 |
- Loss: 0.6514
|
| 25 |
- Accuracy: 0.625
|
|
@@ -58,7 +58,7 @@ More information needed
|
|
| 58 |
|
| 59 |
## Training and evaluation data
|
| 60 |
|
| 61 |
-
|
| 62 |
|
| 63 |
## Training procedure
|
| 64 |
|
|
|
|
| 19 |
|
| 20 |
# tinyllama_rm_sentiment_1b
|
| 21 |
|
| 22 |
+
This model is a fine-tuned version of [TinyLlama/TinyLlama_v1.1](https://huggingface.co/TinyLlama/TinyLlama_v1.1) on https://huggingface.co/datasets/trl-internal-testing/sentiment-trl-style.
|
| 23 |
It achieves the following results on the evaluation set:
|
| 24 |
- Loss: 0.6514
|
| 25 |
- Accuracy: 0.625
|
|
|
|
| 58 |
|
| 59 |
## Training and evaluation data
|
| 60 |
|
| 61 |
+
https://huggingface.co/datasets/trl-internal-testing/sentiment-trl-style
|
| 62 |
|
| 63 |
## Training procedure
|
| 64 |
|