Update README.md
Browse files
README.md
CHANGED
@@ -25,7 +25,7 @@ This instruction model was built via parameter-efficient QLoRA finetuning of [ll
|
|
25 |
|
26 |
We use state-of-the-art [Language Model Evaluation Harness](https://github.com/EleutherAI/lm-evaluation-harness) to run the benchmark tests above, using the same version as Hugging Face's [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
|
27 |
|
28 |
-
### Helpful
|
29 |
|
30 |
* Model license: Llama 2 Community License Agreement
|
31 |
* Basic usage: [notebook](assets/basic_inference_llama_2_70b_dolphin.ipynb)
|
@@ -33,6 +33,12 @@ We use state-of-the-art [Language Model Evaluation Harness](https://github.com/E
|
|
33 |
* Loss curves: [plot](https://huggingface.co/dfurman/llama-2-70b-dolphin-peft#finetuning-description)
|
34 |
* Runtime stats: [table](https://huggingface.co/dfurman/llama-2-70b-dolphin-peft#runtime-tests)
|
35 |
|
|
|
|
|
|
|
|
|
|
|
|
|
36 |
### Example prompts and responses
|
37 |
|
38 |
Example 1:
|
@@ -112,7 +118,7 @@ Example 3:
|
|
112 |
|
113 |
<br>
|
114 |
|
115 |
-
## Model
|
116 |
|
117 |
The architecture is a modification of a standard decoder-only transformer.
|
118 |
|
@@ -129,22 +135,13 @@ The llama-2-70b models have been modified from a standard transformer in the fol
|
|
129 |
| sequence length | 4096 |
|
130 |
| grouped-query attention | ✔️ |
|
131 |
|
132 |
-
|
133 |
-
## Finetuning Description
|
134 |
-
|
135 |
-
This model was trained on a single H100 (80 GB PCIe) for about 17 hours using the [Lambda Labs](https://cloud.lambdalabs.com/instances) platform.
|
136 |
-
|
137 |
-
![loss curves](https://raw.githubusercontent.com/daniel-furman/sft-demos/main/assets/jul_24_23_1_14_00_log_loss_curves_llama-2-70b-dolphin.png)
|
138 |
-
|
139 |
-
The above loss curve was generated from the run's private wandb.ai log.
|
140 |
-
|
141 |
-
## PreTraining Data
|
142 |
|
143 |
For more details on the pretraining process, see [Llama-2-70b-hf](https://huggingface.co/meta-llama/Llama-2-70b-hf).
|
144 |
|
145 |
The data was tokenized using the [Llama-2-70b-hf](https://huggingface.co/meta-llama/Llama-2-70b-hf) tokenizer.
|
146 |
|
147 |
-
## Limitations and
|
148 |
|
149 |
_The following language is modified from [EleutherAI's GPT-NeoX-20B](https://huggingface.co/EleutherAI/gpt-neox-20b)_
|
150 |
|
@@ -152,7 +149,7 @@ This model can produce factually incorrect output, and should not be relied on t
|
|
152 |
This model was trained on various public datasets.
|
153 |
While great efforts have been taken to clean the pretraining data, it is possible that this model could generate lewd, biased or otherwise offensive outputs.
|
154 |
|
155 |
-
## How to
|
156 |
|
157 |
Basic usage: [notebook](assets/basic_inference_llama_2_70b_dolphin.ipynb)
|
158 |
|
|
|
25 |
|
26 |
We use state-of-the-art [Language Model Evaluation Harness](https://github.com/EleutherAI/lm-evaluation-harness) to run the benchmark tests above, using the same version as Hugging Face's [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).
|
27 |
|
28 |
+
### Helpful links
|
29 |
|
30 |
* Model license: Llama 2 Community License Agreement
|
31 |
* Basic usage: [notebook](assets/basic_inference_llama_2_70b_dolphin.ipynb)
|
|
|
33 |
* Loss curves: [plot](https://huggingface.co/dfurman/llama-2-70b-dolphin-peft#finetuning-description)
|
34 |
* Runtime stats: [table](https://huggingface.co/dfurman/llama-2-70b-dolphin-peft#runtime-tests)
|
35 |
|
36 |
+
## Loss curve
|
37 |
+
|
38 |
+
![loss curves](https://raw.githubusercontent.com/daniel-furman/sft-demos/main/assets/jul_24_23_1_14_00_log_loss_curves_llama-2-70b-dolphin.png)
|
39 |
+
|
40 |
+
The above loss curve was generated from the run's private wandb.ai log.
|
41 |
+
|
42 |
### Example prompts and responses
|
43 |
|
44 |
Example 1:
|
|
|
118 |
|
119 |
<br>
|
120 |
|
121 |
+
## Model description
|
122 |
|
123 |
The architecture is a modification of a standard decoder-only transformer.
|
124 |
|
|
|
135 |
| sequence length | 4096 |
|
136 |
| grouped-query attention | ✔️ |
|
137 |
|
138 |
+
## PreTraining data
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
139 |
|
140 |
For more details on the pretraining process, see [Llama-2-70b-hf](https://huggingface.co/meta-llama/Llama-2-70b-hf).
|
141 |
|
142 |
The data was tokenized using the [Llama-2-70b-hf](https://huggingface.co/meta-llama/Llama-2-70b-hf) tokenizer.
|
143 |
|
144 |
+
## Limitations and biases
|
145 |
|
146 |
_The following language is modified from [EleutherAI's GPT-NeoX-20B](https://huggingface.co/EleutherAI/gpt-neox-20b)_
|
147 |
|
|
|
149 |
This model was trained on various public datasets.
|
150 |
While great efforts have been taken to clean the pretraining data, it is possible that this model could generate lewd, biased or otherwise offensive outputs.
|
151 |
|
152 |
+
## How to use
|
153 |
|
154 |
Basic usage: [notebook](assets/basic_inference_llama_2_70b_dolphin.ipynb)
|
155 |
|