File size: 2,213 Bytes
3103e75 62d8964 7de5676 62d8964 3103e75 64afd2f |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 |
---
license: apache-2.0
library_name: transformers
pipeline_tag: text-generation
---
# ibleducation/ibl-tutoring-neural-chat-7B
ibleducation/ibl-tutoring-neural-chat-7B is a model finetuned on top of Intel/neural-chat-7b-v1-1.
This model is finetuned to give responses in a way befitting of a professional teacher.
It is finetuned to exhibit characteristics and virtues such as compassion, encouragement, friendliness and more.
## Benchmarks
| Task |Version| Metric |Value | |Stderr|
|-------------|------:|--------|-----:|---|-----:|
|hellaswag | 0|acc |0.5355|± |0.0050|
| | |acc_norm|0.6977|± |0.0046|
|truthfulqa_mc| 1|mc1 |0.2876|± |0.0158|
| | |mc2 |0.4555|± |0.0158|
## Model Details
- **Developed by:** [IBL Education](https://ibl.ai)
- **Base Model:** [Intel/neural-chat-7b-v1-1](https://huggingface.co/ibleducation/ibl-tutoring-neural-chat-7B
- **Language:** English
- **Finetuned from weights:** [Intel/neural-chat-7b-v1-1](https://huggingface.co/Intel/neural-chat-7b-v1-1)
- **Finetuned on data:**
- ibl-best-practices-instructor-dataset (private)
- **Model License:** Apache 2.0
## How to Use ibl-tutoring-chat-7B Model from Python Code (HuggingFace transformers) ##
### Install the necessary packages
Requires: [transformers](https://pypi.org/project/transformers/) 4.31.0 , and [accelerate](https://pypi.org/project/accelerate/) 0.23.0 or later.
```shell
pip install transformers==4.31.0
pip install accelerate==0.23.0
```
### You can then try the following example code
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
import transformers
import torch
model_id = "ibleducation/ibl-tutoring-neural-chat-7B"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
model_id,
device_map="auto",
trust_remote_code=True,
)
pipeline = transformers.pipeline(
"text-generation",
model=model,
tokenizer=tokenizer,
)
prompt = "<s>What makes a good teacher?</s>"
response = pipeline(prompt)
print(response['generated_text'])
```
**Important** - Use the prompt template below for ibl-tutoring-chat-7B:
```
<s>{prompt}</s>
```
|